Search results for: squared prediction risk

Authors: Saiakhil Chilaka

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Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.

Keywords: juvenile, justice system, data analysis, SHAP

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Authors: Amal A. Mashali, Omar Eltaweel, Elerian Ekladious

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Stature of an individual has an important role in identification, which is often required in medico-legal practice. The estimation of stature is an important step in the identification of dismembered remains or when only a part of a skeleton is only available as in major disasters or with mutilation. There is no published data on anthropological data among Jordanian population. The present study was designed in order to find out relationship of stature to some anthropometric measures among a sample of Jordanian population and to determine the most accurate and reliable one in predicting the stature of an individual. A cross sectional study was conducted on 336 adult healthy volunteers , free of bone diseases, nutritional diseases and abnormalities in the extremities after taking their consent. Students of Faculty of Medicine, Mutah University helped in collecting the data. The anthropometric measurements (anatomically defined) were stature, humerus length, hand length and breadth, foot length and breadth, foot index and knee height on both right and left sides of the body. The measurements were typical on both sides of the bodies of the studied samples. All the anthropologic data showed significant relation with age except the knee height. There was a significant difference between male and female measurements except for the foot index where F= 0.269. There was a significant positive correlation between the different measures and the stature of the individuals. Three equations were developed for estimation of stature. The most sensitive measure for prediction of a stature was found to be the humerus length.

Keywords: foot index, foot length, hand length, humerus length, stature

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Authors: S. Kampeephat, P. Krachodnok, R. Wongsan

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The conventional rectangular horn has been used for microwave antenna a long time. Its gain can be increased by enlarging the construction of horn to flare exponentially. This paper presents a study of the shaped woodpile Electromagnetic Band Gap (EBG) to improve its gain for conventional horn without construction enlargement. The gain enhancement synthesis method for shaped woodpile EBG that has to transfer the electromagnetic fields from aperture of a horn antenna through woodpile EBG is presented by using the variety of shaped woodpile EBGs such as planar, triangular, quadratic, circular, gaussian, cosine, and squared cosine structures. The proposed technique has the advantages of low profile, low cost for fabrication and light weight. The antenna characteristics such as reflection coefficient (S11), radiation patterns and gain are simulated by utilized A Computer Simulation Technology (CST) software. With the proposed concept, an antenna prototype was fabricated and experimented. The S11 and radiation patterns obtained from measurements show a good impedance matching and a gain enhancement of the proposed antenna. The gain at dominant frequency of 10 GHz is 25.6 dB, application for X- and Ku-Band Radar, that higher than the gain of the basic rectangular horn antenna around 8 dB with adding only one appropriated EBG structures.

Keywords: conventional rectangular horn antenna, electromagnetic band gap, gain enhancement, X- and Ku-band radar

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Authors: Gary Peach, Furqan Hameed

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Musaimeer outfall tunnel is one of the longest storm water tunnels in the world, with a total length of 10.15 km. The tunnel will accommodate surface and rain water received from the drainage networks from 270 km of urban areas in southern Doha with a pumping capacity of 19.7m³/sec. The tunnel is excavated by Tunnel Boring Machine (TBM) through Rus Formation, Midra Shales, and Simsima Limestone. Water inflows at high pressure, complex mixed ground, and weaker ground strata prone to karstification with the presence of vertical and lateral fractures connected to the sea bed were also encountered during mining. In addition to pre-tender geotechnical investigations, the Contractor carried out a supplementary offshore geophysical investigation in order to fine-tune the existing results of geophysical and geotechnical investigations. Electric resistivity tomography (ERT) and Seismic Reflection survey was carried out. Offshore geophysical survey was performed, and interpretations of rock mass conditions were made to provide an overall picture of underground conditions along the tunnel alignment. This allowed the critical tunnelling area and cutter head intervention to be planned accordingly. Karstification was monitored with a non-intrusive radar system facility installed on the TBM. The Boring Electric Ahead Monitoring(BEAM) was installed at the cutter head and was able to predict the rock mass up to 3 tunnel diameters ahead of the cutter head. BEAM system was provided with an online system for real time monitoring of rock mass condition and then correlated with the rock mass conditions predicted during the interpretation phase of offshore geophysical surveys. The further correlation was carried by Samples of the rock mass taken from tunnel face inspections and excavated material produced by the TBM. The BEAM data was continuously monitored to check the variations in resistivity and percentage frequency effect (PFE) of the ground. This system provided information about rock mass condition, potential karst risk, and potential of water inflow. BEAM system was found to be more than 50% accurate in picking up the difficult ground conditions and faults as predicted in the geotechnical interpretative report before the start of tunnelling operations. Upon completion of the project, it was concluded that the combined use of different geophysical investigation results can make the execution stage be carried out in a more confident way with the less geotechnical risk involved. The approach used for the prediction of rock mass condition in Geotechnical Interpretative Report (GIR) and Geophysical Reflection and electric resistivity tomography survey (ERT) Geophysical Reflection surveys were concluded to be reliable as the same rock mass conditions were encountered during tunnelling operations.

Keywords: tunnel boring machine (TBM), subsea, karstification, seismic reflection survey

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: M. A. Peribanez, G. Illan, I. De Blas, A. Muniesa, I. Ruiz-Zarzuela

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Intensive aquaculture is commonly associated with increased incidence of parasites. However, in Spain, the recent intensification of cyprinid production has not led to knowledge of the parasites that develop in the aquaculture facilities, the factors that affect their development and spread and the transmission between wild and cultivated fish species. The present study focuses on the knowledge of environmental factors, as well as host dependent factors, and their possible influence as risk factors in the incidence and intensity of parasitic infections. This work was conducted in the Duero River Basin, NW Spain. A total of 114 tenches (Tinca tinca) were caught in a fish farm and 667 specimens belonging to six species of cyprinid, not tench, in five rivers. An exhaustive search and microscopic identification of protozoa on skin and gills were carried out. Physical, chemical, and biological parameters of water samples from the capture points were determined. Only two ectoprotozoa were identified, Ichthyophthirius multifiliis and Tripartiella sp. In I. multifiliis, a high intensity of infection (more than 40 parasites on the body surface and more than 80 on gills) was determined in farmed tench (14%) and in Iberian barbel (Luciobarbus bocagei) (91%) and Duero nase (Pseudochondrostoma duriense) (71%) of middle stretches of rivers. The prevalence was similar between farmed tenches and cyprinids of middle courses. Tripartiella sp. was only found in barbels (prevalence in middle stretches, 0.7%) and in farmed tenches (63%), this species resulting in a high risk factor (odds ratio, OR= 1143) in the presence of the ciliate. There were no differences between the two species relative to the intensity of parasitization. Some of the physical, chemical and microbiological water quality parameters appear to be risk factors in the presence of I. multifiliis, with maximum OR of 8. Nevertheless, in Tripartiella sp., the risk is multiplied by 720 when the pH value exceeds 8.4, if we consider the total of the data, and it is increased more than 500 times if we only consider the values recorded in the fish farm (529 by nitrates > 3 mg/l; 530 by total coliforms > 100 CFU/100 ml). However, the high prevalence and risk of infection by I. multifiliis and Tripartiella sp. in fish farms should be related to environmental factors that dependent upon sampling point rather than in direct influence of the physical-chemical and biological parameters of the water. The high pH value recorded in the fish farm (9.62 ± 0.76) is the only parameter that we consider may have a substantial direct influence. Chronic exposure to alkaline pH levels can be a chronic stress generator, predisposing to parasitization by Tripartiella sp. In conclusion, often minor changes in ecosystem conditions, both natural and man-made, can modify the host-parasite relationship, resulting in an increase in the prevalence and intensity of parasitic infections in populations of cyprinids, sometimes causing disease outbreaks.

Keywords: cyprinids, fish, parasites, protozoa, risk factors

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Authors: Francesco Pandolfi, Georgios Baltzopoulos, Iunio Iervolino

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The impact of extreme winds on industrial assets and the built environment is gaining increasing attention from stakeholders, including the corporate insurance industry. This has led to a progressively more in-depth study of building vulnerability and fragility to wind. Wind vulnerability models are used in probabilistic risk assessment to relate a loss metric to an intensity measure of the natural event, usually a gust or a mean wind speed. In fact, vulnerability models can be integrated with the wind hazard, which consists of associating a probability to each intensity level in a time interval (e.g., by means of return periods) to provide an assessment of future losses due to extreme wind. This has also given impulse to the world- and regional-scale wind hazard studies.Another approach often adopted for the probabilistic description of building vulnerability to the wind is the use of fragility functions, which provide the conditional probability that selected building components will exceed certain damage states, given wind intensity. In fact, in wind engineering literature, it is more common to find structural system- or component-level fragility functions rather than wind vulnerability models for an entire building. Loss assessment based on component fragilities requires some logical combination rules that define the building’s damage state given the damage state of each component and the availability of a consequence model that provides the losses associated with each damage state. When risk calculations are based on numerical simulation of a structure’s behavior during extreme wind scenarios, the interaction of component fragilities is intertwined with the computational procedure. However, simulation-based approaches are usually computationally demanding and case-specific. In this context, the present work introduces the ExtReMe wind risk assESsment prototype Software, ERMESS, which is being developed at the University of Naples Federico II. ERMESS is a wind risk assessment tool for insurance applications to industrial facilities, collecting a wide assortment of available wind vulnerability models and fragility functions to facilitate their incorporation into risk calculations based on in-built or user-defined wind hazard data. This software implements an alternative method for building-specific risk assessment based on existing component-level fragility functions and on a number of simplifying assumptions for their interactions. The applicability of this alternative procedure is explored by means of an illustrative proof-of-concept example, which considers four main building components, namely: the roof covering, roof structure, envelope wall and envelope openings. The application shows that, despite the simplifying assumptions, the procedure can yield risk evaluations that are comparable to those obtained via more rigorous building-level simulation-based methods, at least in the considered example. The advantage of this approach is shown to lie in the fact that a database of building component fragility curves can be put to use for the development of new wind vulnerability models to cover building typologies not yet adequately covered by existing works and whose rigorous development is usually beyond the budget of portfolio-related industrial applications.

Keywords: component wind fragility, probabilistic risk assessment, vulnerability model, wind-induced losses

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Authors: Ayedun Hassan, Ayadi Odunayo Peter

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The ancient city of Abeokuta has been supplied with pipe borne water since 1911, yet, a continuous increase in population and unplanned city expansion makes water a very precious and scarce commodity. The government reserved areas (GRA’s) are well planned, and public water supply is available; however, the sub-urban areas consist of scattered structures with individuals trying to source water by digging wells and boreholes. The geology of the city consists of basement rock which makes digging wells and boreholes very difficult. The present study was conducted to assess the risk arising from the consumption of toxic elements in the groundwater of Abeokuta, Ogun State, Nigeria. Forty-five groundwater samples were collected from nine different areas of Abeokuta and analyzed for physicochemical parameters and toxic elements. The physicochemical parameters were determined using standard methods, while the toxic elements were determined using Inductively Coupled Plasma-Mass Spectrometer (ICP/MS). Ninety-six percent (96%) of the water sample has pH < 6.5, and 11% has conductivity > 250 µSCm⁻¹ limits in drinking water as recommended by WHO. Seven percent (7%) of the samples have Pb concentration >10 µgL⁻¹ while 75% have Al concentration >200 µgL⁻¹ recommended by WHO. The order for risk of cancer from different area of Abeokuta are Cd²⁺ > As³⁺ > Pb²⁺ > Cr⁶⁺ for Funaab, Camp and Obantoko; As³⁺ > Cd²⁺ > Pb²⁺ > Cr⁶⁺ for Ita Osin, Isale Igbein, Ake and Itoku; Cd²⁺ >As > Cr⁶⁺ > Pb²⁺ for Totoro; Pb²⁺ > Cd²⁺ > As³⁺ > Cr⁶⁺ for Idiaba. The order of non-cancer hazard index (HI) calculated for groundwater of Abeokuta City are Cd²⁺ > As³⁺ > Mn²⁺ > Pb²⁺ > Ni²⁺ and were all greater than one, which implies susceptibility to other illnesses. The sources of these elements are the rock and inappropriate waste disposal method, which leached the elements into the groundwater. A combination of sources from food will accumulate these elements in the human body system. Treatment to remove Al and Pb is necessary, while the method of water distribution should be reviewed to ensure access to potable water by the residents.

Keywords: Abeokuta, groundwater, Nigeria, risk

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Authors: Huma Naqeeb

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Epidemiological studies have shown the robust link between breast cancer and dietary pattern. There has been no previous study conducted in Pakistan, which specifically focuses on dietary patterns among breast cancer women. This study aims to examine the association of breast cancer with dietary patterns among Pakistani women. This case-control research was carried in multiple tertiary care facilities. Newly diagnosed primary breast cancer patients were recruited as cases (n = 408); age matched controls (n = 408) were randomly selected from the general population. Data on required parameters were systematically collected using subjective and objective tools. Factor and Principal Component Analysis (PCA) techniques were used to extract women’s dietary patterns. Four dietary patterns were identified based on eigenvalue >1; (i) veg-ovo-fish, (ii) meat-fat-sweet, (iii) mix (milk and its products, and gourds vegetables) and (iv) lentils - spices. Results of the multiple regressions were displayed as adjusted odds ratio (Adj. OR) and their respective confidence intervals (95% CI). After adjusted for potential confounders, veg-ovo-fish dietary pattern was found to be robustly associated with a lower risk of breast cancer among women (Adj. OR: 0.68, 95%CI: (0.46-0.99, p<0.01). The study findings concluded that attachment to the diets majorly composed of fresh vegetables, and high quality protein sources may contribute in lowering the risk of breast cancer among women.

Keywords: breast cancer, dietary pattern, women, principal component analysis

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Authors: Idrissa Kayijuka

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The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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Authors: Zhizhong Yuan, Lili Wang, Chenya Zheng, Wuqi Yang

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How to encourage and support peer-to-peer (P2P) network lending, and effectively monitor the risk of P2P network lending, has become the focus of the Chinese government departments, industrialists, experts and scholars in recent years. The reason is that this convenient online micro-credit service brings a series of credit risks and other issues. Avoiding the risks brought by the P2P network lending model, it can better play a benign role and help China's small and medium-sized private enterprises with vigorous development to solve the capital needs; otherwise, it will bring confusion to the normal financial order. As a form of financial services, P2P network lending has injected new blood into China's non-government finance in the past ten years, and has found a way out for idle funds and made up for the shortage of traditional financial services in China. However, it lacks feasible measures in credit evaluation and government supervision. This paper collects a large amount of data about P2P network lending of China. The data collection comes from the official media of the Chinese government, the public achievements of existing researchers and the analysis and collation of correlation data by the authors. The research content of this paper includes literature review; the current situation of China's P2P network lending development; the risk analysis of P2P network lending in China; the risk prevention strategy of P2P network lending in China. The focus of this paper is to try to find a specific program to strengthen supervision and avoid risks from the perspective of government regulators, operators of P2P network lending platform, investors and users of funds. These main measures include: China needs to develop self-discipline organization of P2P network lending industry and formulate self-discipline norms as soon as possible; establish a regular information disclosure system of P2P network lending platform; establish censorship of credit rating of borrowers; rectify the P2P network lending platform in compliance through the implementation of bank deposition. The results and solutions will benefit all the P2P network lending platforms, creditors, debtors, bankers, independent auditors and government agencies of China and other countries.

Keywords: peer-to-peer(P2P), regulation, risk prevention, supervision

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Authors: Collen Kawiya

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In an effort of reducing post-harvest losses and improving the supply of quality fish products in Malawi, the fish solar tent dryers have been designed in the southern part of Lake Malawi for processing small fish species under the project of Cultivate Africa’s Future (CultiAF). This study was done to promote the adoption of the fish solar tent dryers by the many small scale fish processors in Malawi through the assessment of the economic viability of these dryers. With the use of the project’s baseline survey data, a business model for a constructed ‘ready for use’ solar tent dryer was developed where investment appraisal techniques were calculated in addition with the sensitivity analysis. The study also conducted a risk analysis through the use of the Monte Carlo simulation technique and a probabilistic net present value was found. The investment appraisal results showed that the net present value was US$8,756.85, the internal rate of return was 62% higher than the 16.32% cost of capital and the payback period was 1.64 years. The sensitivity analysis results showed that only two input variables influenced the fish solar dryer investment’s net present value. These are the dried fish selling prices that were correlating positively with the net present value and the fresh fish buying prices that were negatively correlating with the net present value. Risk analysis results showed that the chances that fish processors will make a loss from this type of investment are 17.56%. It was also observed that there exist only a 0.20 probability of experiencing a negative net present value from this type of investment. Lastly, the study found that the net present value of the fish solar tent dryer’s investment is still robust in spite of any changes in the levels of investors risk preferences. With these results, it is concluded that the fish solar tent dryers in Malawi are an economically viable investment because they are able to improve the returns in the fish processing activity. As such, fish processors need to adopt them by investing their money to construct and use them.

Keywords: investment appraisal, risk analysis, sensitivity analysis, solar tent drying

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Authors: Benson Ade Eniola Afere

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Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance.

Keywords: classical polynomial kernels, cluster of families, global error, hybrid Kernels, Kernel density estimation, Monte Carlo simulation

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Authors: Daniel M. Wolff, Patricia Gray, Rafael de la Parra Venegas

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An unsupervised machine listening system is constructed and applied to a dataset of 17,195 30-second marine hydrophone recordings. The system is then heuristically supplemented with anecdotal listening, contextual recording information, and supervised learning techniques to reduce the number of false positives. Features for classification are assembled by extracting the following data from each of the audio files: the spectral centroid, root-mean-squared values for each frequency band of a 10-octave filter bank, and mel-frequency cepstral coefficients in 5-second frames. In this way both time- and frequency-domain information are contained in the features to be passed to a clustering algorithm. Classification is performed using the k-means algorithm and then a k-nearest neighbors search. Different values of k are experimented with, in addition to different combinations of the available feature sets. Hypothesized class labels are 'primarily anthrophony' and 'primarily biophony', where the best class result conforming to the former label has 104 members after heuristic pruning. This demonstrates how a large audio dataset has been made more tractable with machine learning techniques, forming the foundation of a framework designed to acoustically monitor and gauge biological and anthropogenic activity in a marine environment.

Keywords: anthrophony, hydrophone, k-means, machine learning

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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Authors: Alireza Dantism

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Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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Authors: Omar Dib, Rita Yaacoub, Luc Eveleigh, Nathalie Locquet, Hussein Dib, Ali Bassal, Christophe B. Y. Cordella

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The potential of front-face fluorescence coupled with chemometric techniques, namely parallel factor analysis (PARAFAC) and multiple linear regression (MLR) as a rapid analysis tool to characterize Lebanese virgin olive oils was investigated. Fluorescence fingerprints were acquired directly on 102 Lebanese virgin olive oil samples in the range of 280-540 nm in excitation and 280-700 nm in emission. A PARAFAC model with seven components was considered optimal with a residual of 99.64% and core consistency value of 78.65. The model revealed seven main fluorescence profiles in olive oil and was mainly associated with tocopherols, polyphenols, chlorophyllic compounds and oxidation/hydrolysis products. 23 MLR regression models based on PARAFAC scores were generated, the majority of which showed a good correlation coefficient (R > 0.7 for 12 predicted variables), thus satisfactory prediction performances. Acid values, peroxide values, and Delta K had the models with the highest predictions, with R values of 0.89, 0.84 and 0.81 respectively. Among fatty acids, linoleic and oleic acids were also highly predicted with R values of 0.8 and 0.76, respectively. Factors contributing to the model's construction were related to common fluorophores found in olive oil, mainly chlorophyll, polyphenols, and oxidation products. This study demonstrates the interest of front-face fluorescence as a promising tool for quality control of Lebanese virgin olive oils.

Keywords: front-face fluorescence, Lebanese virgin olive oils, multiple Linear regressions, PARAFAC analysis

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Authors: Abhishikta Ghosh Roy

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Breast cancer is the most common malignancy among women globally, including India. Human breast cancer results from the genetic and environmental interaction. The present study attempts to understand the molecular heterogeneity of BRCA1 and BRCA2 genes, as well as to understand the association of various lifestyle and reproductive variables for the Breast Cancer risk. The study was conducted amongst 110 patients and 128 controls with total DNA sequencing of flanking and coding regions of BRCA1 BRCA2 genes that revealed ten Single Nucleotide Polymorphisms (SNPs) (6 novels). The controls selected for the study were age, sex and ethnic group matched. After written and informed consent biological samples were collected from the subjects. After detailed molecular analysis, significant (p < 0.005) molecular heterogeneity is revealed in terms of SNPs in BRCA1 (4 Exonic & 1 Intronic) and BRCA2 (2exonic and 3 Intronic) genes. The augmentation study investigated significant (p < 0.05) association with positive family history, early age at menarche, irregular menstrual periods, menopause, prolong contraceptive use, nulliparity, history of abortions, consumption of alcohol and smoking for breast cancer risk. To the best of authors knowledge, this study is the first of its kind, envisaged that the identification of the SNPs and modification of the lifestyle factors might aid to minimize the risk among the Bengalee Hindu females.

Keywords: breast cancer, BRCA, lifestyle, India

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Authors: Maha Awad M. Almuttairi

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This research aimed to measure the impact of the use of a mobile learning (iTunes U) app for the development of metacognition skills delivered in the enrichment program offered to gifted students at the secondary level in Jeddah. The author targeted a group of students on an experimental scale to evaluate the achievement. The research sample consisted of a group of 38 gifted female students. The scale of evaluation of the metacognition skills used to measure the performance of students in the enrichment program was as follows: Satisfaction scale for the assessment of the technique used and the final product form after completion of the program. Appropriate statistical treatment used includes Paired Samples T-Test Cronbach’s alpha formula and eta squared formula. It was concluded in the results the difference of α≤ 0.05, which means the performance of students in the skills of metacognition in favor of using iTunes U. In light of the conclusion of the experiment, a number of recommendations and suggestions were present; the most important benefit of mobile learning applications is to provide enrichment programs for gifted students in the Kingdom of Saudi Arabia, as well as conducting further research on mobile learning and gifted student teaching.

Keywords: enrichment program, gifted students, metacognition skills, mobile learning

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Authors: J. Vinay , Kusumbati Besra, Niharika Pattnaik, Shivaram Prasad Singh, Manjusha Dixit

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Gallbladder cancer (GBC) is rare but highly malignant cancer; its prevalence is more in certain geographical regions and ethnic groups, which include the Northern and Eastern states of India. Previous studies in India have reported genetic predisposition as one of the risk factors in GBC pathogenesis. Although the matrix metalloproteinase-14 (MMP14) is a well-known modulator of the tumor microenvironment and tumorigenesis and TCGA data also suggests its upregulation yet, its role in the genetic predisposition for GBC is completely unknown. We elucidated the role of MMP14 promoter variants as genetic risk factors and their implications in expression modulation. We screened MMP14 promoter variants association with GBC using Sanger’s sequencing in approximately 300 GBC and 300 control subjects and 26 GBC tissue samples of Indian ethnicity. The immunohistochemistry was used to check the MMP14 protein expression in GBC tissue samples. The role of promoter variants on expression levels was elucidated using a luciferase reporter assay. The variants rs1004030 (p-value = 0.0001) and rs1003349 (p-value = 0.0008) were significantly associated with gallbladder cancer. The luciferase assay in two different cell lines, HEK-293 (p = 0.0006) and TGBC1TKB (p = 0.0036) showed a significant increase in relative luciferase activity in the presence of risk alleles for both the single nucleotide polymorphisms (SNPs). Similarly, genotype-phenotype correlation in patients samples confirmed that the presence of risk alleles at rs1004030 and rs1003349 increased MMP14 expression. Overall, this study unravels the genetic association of MMP14 promoter variants with gallbladder cancer, which may contribute to pathogenesis by increasing its expression.

Keywords: gallbladder cancer, matrix metalloproteinase-14, single nucleotide polymorphism, case control study, genetic association study

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: I. Boroňová, J. Bernasovská, J. Kmec, E. Petrejčíková

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Dilated cardiomyopathy (DCM) is a severe cardiovascular disorder characterized by progressive systolic dysfunction due to cardiac chamber dilatation and inefficient myocardial contractility often leading to chronic heart failure. Recently, a genome-wide association studies (GWASs) on DCM indicate that the ZBTB17 gene rs10927875 single nucleotide polymorphism is associated with DCM. The aim of the study was to identify the distribution of ZBTB17 gene rs10927875 polymorphism in 50 Slovak patients with DCM and 80 healthy control subjects using the Custom Taqman®SNP Genotyping assays. Risk factors detected at baseline in each group included age, sex, body mass index, smoking status, diabetes and blood pressure. The mean age of patients with DCM was 52.9±6.3 years; the mean age of individuals in control group was 50.3±8.9 years. The distribution of investigated genotypes of rs10927875 polymorphism within ZBTB17 gene in the cohort of Slovak patients with DCM was as follows: CC (38.8%), CT (55.1%), TT (6.1%), in controls: CC (43.8%), CT (51.2%), TT (5.0%). The risk allele T was more common among the patients with dilated cardiomyopathy than in normal controls (33.7% versus 30.6%). The differences in genotype or allele frequencies of ZBTB17 gene rs10927875 polymorphism were not statistically significant (p=0.6908; p=0.6098). The results of this study suggest that ZBTB17 gene rs10927875 polymorphism may be a risk factor for susceptibility to DCM in Slovak patients with DCM. Studies of numerous files and additional functional investigations are needed to fully understand the roles of genetic associations.

Keywords: ZBTB17 gene, rs10927875 polymorphism, dilated cardiomyopathy, cardiovascular disorder

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Authors: Samaneh Abolli, Kamyar Yaghmaeian, Ali Arab Aradani, Mahmood Alimohammadi

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The main route of fluoride uptake is drinking water. Fluoride absorption in the acceptable range (0.5-1.5 mg L-¹) is suitable for the body, but it's too much consumption can have irreversible health effects. To compare fluoride concentration with the WHO guidelines, 112 water samples were taken from groundwater aquifers in 22 villages of Garmsar County, the central part of Iran, during 2018 to 2019.Fluoride concentration was measured by the SPANDS method, and its non-carcinogenic impacts were calculated using EDI and HQ. The statistical population was divided into four categories of infant, children, teenagers, and adults. Linear regression and Spearman rank correlation coefficient tests were used to investigate the relationships between the well's depth and fluoride concentration in the water samples. The annual mean concentrations of fluoride in 2018 and2019 were 0.75 and 0.64 mg -¹ and, the fluoride mean concentration in the samples classifying the cold and hot seasons of the studied years was 0.709 and 0.689 mg L-¹, respectively. The amount of fluoride in 27% of the samples in both years was less than the acceptable minimum (0.5 mg L-¹). Also, 11% of the samples in2018 (6 samples) had fluoride levels higher than 1.5 mg L-¹. The HQ showed that the children were vulnerable; teenagers and adults were in the next ranks, respectively. Statistical tests showed a reverse and significant correlation (R2 = 0.02, < 0.0001) between well depth and fluoride content. The border between the usefulness/harmfulness of fluoride is very narrow and requires extensive studies.

Keywords: fluoride, groundwater, health risk assessment, hazard quotient, Garmsar

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Authors: Abdulquadri Ade Bilau, Richard Ajayi Jimoh, Adejoh Amodu Adaji

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The increasing exposures to natural hazards have continued to severely impair on the built environment causing huge fatalities, mass damage and destruction of housing and civil infrastructure while leaving psychosocial impacts on affected communities. The 2012 flood disaster in Nigeria which affected over 7 million inhabitants in 30 of the 36 states resulted in 363 recorded fatalities with about 600,000 houses and a number of civil infrastructure damaged or destroyed. In Kogi State, over 500 thousand people were displaced in 9 out of the 21 local government affected while Ibaji and Lokoja local governments were worst hit. This study identifies the causes and 2012 flood disasters and its effect on housing and livelihood. Personal observation and questionnaire survey were instruments used in carrying out the study and data collected were analysed using descriptive statistical tool. Findings show that the 2012 flood disaster was aided by the gap in hydrological data, sudden dam failure, and inadequate drainage capacity to reduce flood risk. The study recommends that communities residing along the river banks in Lokoja and Ibaji LGAs must be adequately educated on their exposure to flood hazard and mitigation and risk reduction measures such as construction of adequate drainage channel are constructed in affected communities.

Keywords: flood, hazards, housing, risk reduction, vulnerability

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Authors: Alvaro L. Ronco

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Background and purpose: Although our country is a developing one, it has a typical Western meat-rich dietary style. Based on estimates of heme and nonheme iron contents in representative foods, we carried out the present epidemiologic study, with the aim of accurately analyzing dietary iron and its role on CRC risk. Subjects/methods: Patients (611 CRC incident cases and 2394 controls, all belonging to public hospitals of our capital city) were interviewed through a questionnaire including socio-demographic, reproductive and lifestyle variables, and a food frequency questionnaire of 64 items, which asked about food intake 5 years before the interview. The sample included 1937 men and 1068 women. Controls were matched by sex and age (± 5 years) to cases. Food-derived nutrients were calculated from available databases. Total dietary iron was calculated and classified by heme or nonheme source, following data of specific Dutch and Canadian studies, and additionally adjusted by energy. Odds Ratios (OR) and 95% confidence intervals were calculated through unconditional logistic regression, adjusting for relevant potential confounders (education, body mass index, family history of cancer, energy, infusions, and others). A heme/nonheme (H/NH) ratio was created and the interest variables were categorized into tertiles, for analysis purposes. Results: The following risk estimations correspond to the highest tertiles. Total iron intake showed no association with CRC risk neither among men (OR=0.83, ptrend =.18) nor among women (OR=1.48, ptrend =.09). Heme iron was positively associated among men (OR=1.88, ptrend < .001) and for the overall sample (OR=1.44, ptrend =.002), however, it was not associated among women (OR=0.91, ptrend =.83). Nonheme iron showed an inverse association among men (OR=0.53, ptrend < .001) and the overall sample (OR=0.78, ptrend =.04), but was not associated among women (OR=1.46, ptrend =.14). Regarding H/NH ratio, risks increased only among men (OR=2.12, ptrend < .001) but lacked of association among women (OR=0.81, ptrend =.29). Conclusions. We have observed different types of associations between CRC risk and high dietary heme, nonheme and H/NH iron ratio. Therefore, the source of the available iron might be of importance as a link to colorectal carcinogenesis, perhaps pointing to reconsider the animal/plant proportions of this vital mineral within diet. Nevertheless, the different associations observed for each sex, demand further studies in order to clarify these points.

Keywords: chelation, colorectal cancer, heme, iron, nonheme

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Authors: Michael A. Kraus, Navid Pourmoghaddam, Martin Botz, Jens Schneider, Geralt Siebert

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Fragmentation analysis of tempered glass gives insight into the quality of the tempering process and defines a certain degree of safety as well. Different standard such as the European EN 12150-1 or the American ASTM C 1048/CPSC 16 CFR 1201 define a minimum number of fragments required for soda-lime safety glass on the basis of fragmentation test results for classification. This work presents an approach for the glass breakage pattern prediction using a Voronoi Tesselation over Random Fields. The random Voronoi tessellation is trained with and validated against data from several breakage patterns. The fragments in observation areas of 50 mm x 50 mm were used for training and validation. All glass specimen used in this study were commercially available soda-lime glasses at three different thicknesses levels of 4 mm, 8 mm and 12 mm. The results of this work form a Bayesian framework for the training and prediction of breakage patterns of tempered soda-lime glass using a Voronoi Random Field Tesselation. Uncertainties occurring in this process can be well quantified, and several statistical measures of the pattern can be preservation with this method. Within this work it was found, that different Random Fields as basis for the Voronoi Tesselation lead to differently well fitted statistical properties of the glass breakage patterns. As the methodology is derived and kept general, the framework could be also applied to other random tesselations and crack pattern modelling purposes.

Keywords: glass breakage predicition, Voronoi Random Field Tessellation, fragmentation analysis, Bayesian parameter identification

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Authors: Duchduen Bhanthumnavin

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One of the most important characteristics to increase competitive ability in undergraduate students after post COVID-19 era is goal setting and self-control. This correlational study aimes at investigating the influence of psycho-social antecedents on goal setting and self-control in 550 Thai university students. Results from multiple regression analysis revealed that the important predictors of this characteristic were reasoning ability, psychological immunity, attitudes toward competition, core self-evaluation, and family nurture, which yielded 54.28 predictive percentage in the total sample. Moreover, the analysis identified three at-risk groups, namely, male students, low GPA students, and students with siblings. Discussion and implications in general and for specific purposes for the at-risk groups were offered.

Keywords: antecedents, plan and self-control, predictors, university students

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Authors: Charawee Butbumrung

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The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation

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Authors: Byeongju Choi, Sanggil Lee, Kyung-Eun Lee

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Introduction: In the republic of Korea, the number of workers in the beauty industry has been increasing. Because the prevalence of hepatitis B carriers in Korea is higher than in other countries, the risk of blood-borne infection including viral hepatitis B and C, among the workers by using the sharp and contaminated instruments during procedure can be expected among beauty salon workers. However, the health care policies for the workers to prevent the blood-borne infection are not established due to the lack of evidences. Moreover, the workers in hair and nail salon were mostly employed at small businesses, where national mandatory systems or policies for workers’ health management are not applied. In this study, the risk of the viral hepatitis B and C from the job experiencing the hair and nail procedures in the mortality was assessed. Method: We conducted a retrospective review of the job histories and causes of death in the female deaths from 2006-2016. 132,744 of female deaths who had one more job experiences during their lifetime were included in this study. Job histories were assessed using the employment insurance database in Korea Employment Information Service (KEIS) and the causes of death were in death statistics produced by Statistics Korea. Case group (n= 666) who died from viral hepatitis was classified the death having record involved in ‘B15-B19’ as a cause of deaths based on Korean Standard Classification of Diseases(KCD) with the deaths from other causes, control group (n=132,078). The group of the workers in the beauty service industry were defined as the employees who had ever worked in the industry coded as ‘9611’ based on Korea Standard Industry Classification (KSIC) and others were others. Other than job histories, birth year, marital status, education level were investigated from the death statistics. Multiple logistic regression analysis were used to assess the risk of deaths from viral hepatitis in the case and control group. Result: The number of the deaths having ever job experiences at the hair and nail salon was 255. After adjusting confounders of age, marital status and education, the odds ratio(OR) for deaths from viral hepatitis was quite high in the group having experiences with working in the beauty service industry with 3.14(95% confidence interval(CI) 1.00-9.87). Other associated factors with increasing the risk of deaths from viral hepatitis were low education level(OR=1.34, 95% CI 1.04-1.73), married women (OR=1.42, 95% CI 1.02-1.97). Conclusion: The risk of deaths from viral hepatitis were high in the workers in the beauty service industry but not statistically significant, which might attributed from the small number of workers in beauty service industry. It was likely that the number of workers in beauty service industry could be underestimated due to their temporary job position. Further studies evaluating the status and the incidence of viral infection among the workers with consideration of the vertical transmission would be required.

Keywords: beauty service, viral hepatitis, blood-borne infection, viral infection

Procedia PDF Downloads 139

Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

Procedia PDF Downloads 305