Search results for: ADAMS validation

Authors: Tanja Salary

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This study uncovers a gap in the research and adds to the body of knowledge regarding medication errors in a juvenile justice facility. The study includes an introduction to data collected about medication errors in a juvenile justice facility and explores contributing factors that relate to those errors. The data represent electronic incident records of the medication errors that were documented from the years 2011 through 2019. In addition, this study reviews both current and historical research of empirical data about patient safety standards and quality care comparing traditional healthcare facilities to juvenile justice residential facilities. The theoretical/conceptual framework for the research study pertains to Bandura and Adams’s (1977) framework of self-efficacy theory of behavioral change and Mark Friedman’s results-based accountability theory (2005). Despite the lack of evidence in previous studies about addressing medication errors in juvenile justice facilities, this presenter will relay information that adds to the body of knowledge to note the importance of how assessing the potential relationship between medication errors. Implications for more research include recommendations for more education and training regarding increased communication among juvenile justice staff, including nurses, who administer medications to juveniles to ensure adherence to patient safety standards. There are several opportunities for future research concerning other characteristics about factors that may affect medication administration errors within the residential juvenile justice facility.

Keywords: juvenile justice, medication errors, psychotropic medications, behavioral health, juveniles, incarcerated youth, recidivism, patient safety

Procedia PDF Downloads 35

Authors: Zahraa Al Ali, Ammar Abulibdeh, Talal Al-Awadhi, Midhun Mohan, Mohammed Al-Barwani, Mohammed Al-Barwani, Sara Al Nabbi, Meshal Abdullah

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This study aims to evaluate the performance and effectiveness of six spectral water indices - derived from Multispectral sentinel-2 data - to detect soil moisture and inundated area in arid regions to be used as an indicator of mudflow phenomena to predict high-risk areas. Herein, the validation of the performance of spectral indices was conducted using threshold method, spectral curve performance, and soil-line method. These indirect validation techniques play a key role in saving time, effort, and cost, particularly for large-scale and inaccessible areas. It was observed that the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (mNDWI), and RSWIR indices have the potential to detect soil moisture and inundated areas in arid regions. According to the temporal spectral curve performance, the spectral characteristics of water and soil moisture were distinct in the Near infrared (NIR), Short-wave Infrared (SWIR1,2) bands. However, the rate and degree differed between these bands, depending on the amount of water in the soil. Furthermore, the soil line method supported the appropriate selection of threshold values to detect soil moisture. However, the threshold values varied with location, time, season, and between indices. We concluded that considering the factors influencing the behavior of water and soil reflectivity could support decision-makers in identifying high-risk mudflow locations.

Keywords: spectral reflectance curve, soil-line method, spectral indices, Shaheen cyclone

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Authors: Endang Lukitaningsih, Fathul Jannah, Arief R. Hakim, Ratna D. Puspita, Zullies Ikawati

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Rifampicin is a semisynthetic antibiotic derivative of rifamycin B produced by Streptomyces mediterranei. RIF has been used worldwide as first line drug-prescribed throughout tuberculosis therapy. This study aims to develop and to validate an HPLC method couple with a UV detection for determination of rifampicin in spiked human plasma and its application for bioequivalence study. The chromatographic separation was achieved on an RP-C18 column (LachromHitachi, 250 x 4.6 mm., 5μm), utilizing a mobile phase of phosphate buffer/acetonitrile (55:45, v/v, pH 6.8 ± 0.1) at a flow of 1.5 mL/min. Detection was carried out at 337 nm by using spectrophotometer. The developed method was statistically validated for the linearity, accuracy, limit of detection, limit of quantitation, precise and specifity. The specifity of the method was ascertained by comparing chromatograms of blank plasma and plasma containing rifampicin; the matrix and rifampicin were well separated. The limit of detection and limit of quantification were 0.7 µg/mL and 2.3 µg/mL, respectively. The regression curve of standard was linear (r > 0.999) over a range concentration of 20.0 – 100.0 µg/mL. The mean recovery of the method was 96.68 ± 8.06 %. Both intraday and interday precision data showed reproducibility (R.S.D. 2.98% and 1.13 %, respectively). Therefore, the method can be used for routine analysis of rifampicin in human plasma and in bioequivalence study. The validated method was successfully applied in pharmacokinetic and bioequivalence study of rifampicin tablet in a limited number of subjects (under an Ethical Clearance No. KE/FK/6201/EC/2015). The mean values of Cmax, Tmax, AUC(0-24) and AUC(o-∞) for the test formulation of rifampicin were 5.81 ± 0.88 µg/mL, 1.25 hour, 29.16 ± 4.05 µg/mL. h. and 29.41 ± 4.07 µg/mL. h., respectively. Meanwhile for the reference formulation, the values were 5.04 ± 0.54 µg/mL, 1.31 hour, 27.20 ± 3.98 µg/mL.h. and 27.49 ± 4.01 µg/mL.h. From bioequivalence study, the 90% CIs for the test formulation/reference formulation ratio for the logarithmic transformations of Cmax and AUC(0-24) were 97.96-129.48% and 99.13-120.02%, respectively. According to the bioequivamence test guidelines of the European Commission-European Medicines Agency, it can be concluded that the test formulation of rifampicin is bioequivalence with the reference formulation.

Keywords: validation, HPLC, plasma, bioequivalence

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 36

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 57

Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

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We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

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Authors: Jinghua Zhang

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Shaft-tunnel junction is a typical case of the structural nonuniformity in underground structures. The shaft and the tunnel possess greatly different structural features. Even under uniform excitations, they tend to behave discrepantly. Studies on shaft-tunnel junctions are mainly performed numerically. Shaking table tests are also conducted. Although many numerical and experimental data are obtained, an analytical solution still has great merits of gaining more insights into the shaft-tunnel problem. This paper will try to remedy the situation. Since the seismic responses of shaft-tunnel junctions are very related to directions of the excitations, they are studied in two scenarios: the longitudinal-excitation scenario and the transverse-excitation scenario. The former scenario will be addressed in this paper. Given that responses of the tunnel are highly dependent on the shaft, the analytical solutions would be developed firstly for the vertical shaft. Then, the seismic responses of the tunnel would be discussed. Since vertical shafts bear a resemblance to rigid caissons, the solution proposed in this paper is derived by introducing terms of shaft-tunnel and soil-tunnel interactions into equations originally developed for rigid caissons. The validity of the solution is examined by a validation model computed by finite element method. The mutual influence between the shaft and the tunnel is introduced. The soil-structure interactions are discussed parametrically based on the proposed equations. The shaft-tunnel relative displacement and the soil-tunnel relative stiffness are found to be the most important parameters affecting the magnitudes and distributions of the internal forces of the tunnel. A hinge-joint at the shaft-tunnel junction could significantly reduce the degree of stress concentration compared with a rigid joint.

Keywords: analytical solution, longitudinal excitation, numerical validation , shaft-tunnel junction

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Authors: Abubakar-Zagoon Adams, Emmanuel Intsiful, Haruna Zagoon-Sayeed

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Within the Ghanaian context, the promotion of Technical and Vocational Education and Training (TVET) has been faced with many obstacles which are of great concern to national development. One of the obstacles that have been identified as having some negative impact on TVET promotion is the poor public perception of TVET. Poor public perception, as identified in the sub-sectors report in a number of Ghana Education Service reports, has received little attention in both research and the government’s effort to address the poor performance of the TVET sub-sector. This study investigated TVET stakeholders in the Ayawaso-West Municipality in the Greater Accra Region of Ghana to ascertain knowledge of technical and vocational education in Ghana. This study explored parents’ and students’ views and knowledge about technical and vocational education. The study adopted an exploratory research design and a qualitative research approach. Thirty-six (36) participants were selected by employing a purposive sampling technique. Twelve (ten parents and two school personnel) out of the total sample were engaged in key informant interviews, whereas three focus group discussions were conducted with students, eight in each group. The study found that the public has fair knowledge (positive) about TVET, and the other side of the coin knows that TVET is only meant for school dropouts, underprivileged students, and weak academic students. The study recommended that the government should intensify public education on TVET, deliberate investment should be made in TVET infrastructure, as well as proper regulation of the sub-sector.

Keywords: public perception, TVET promotion, socioeconomic, self-employment

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Authors: Amir Reza Heydari, Yaser Jenab

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Coronary artery disease, a common cardiovascular disease, is attributed to the accumulation of cholesterol-based plaques in the coronary arteries, leading to atherosclerosis. This disease is associated with risk factors such as smoking, hypertension, diabetes, and elevated cholesterol levels, contributing to severe clinical consequences, including acute coronary syndromes and myocardial infarction. Treatment approaches such as from lifestyle interventions to surgical procedures like percutaneous coronary intervention and coronary artery bypass surgery. These interventions often employ stents, including bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable vascular scaffolds (BVS), each with its advantages and limitations. Computational tools have emerged as critical in optimizing stent designs and assessing their performance. The aim of this study is to provide an overview of the computational methods of studies based on the finite element (FE) method in the field of coronary stenting and discuss the potential for development and clinical application of stent devices. Additionally, the importance of assessing the ability of computational models is emphasized to represent real-world phenomena, supported by recent guidelines from the American Society of Mechanical Engineers (ASME). Validation processes proposed include comparing model performance with in vivo, ex-vivo, or in vitro data, alongside uncertainty quantification and sensitivity analysis. These methods can enhance the credibility and reliability of in silico simulations, ultimately aiding in the assessment of coronary stent designs in various clinical contexts.

Keywords: atherosclerosis, materials, restenosis, review, validation

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Authors: Sitarrine Thongpussawal, Hui Shao, Clark Gantzer

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Terracing is a conservation practice to reduce erosion and widely used for soil and water conservation throughout the world but is relatively expensive. A modification of the Soil and Water Assessment Tool (called SWAT-Terrace or SWAT-T) explicitly aims to improve the simulation of the hydrological process of erosion from the terraces. SWAT-T simulates erosion from the terraces by separating terraces into three segments instead of evaluating the entire terrace. The objective of this work is to evaluate the terrace benefits on erosion from the Goodwater Creek Experimental Watershed (GCEW) at watershed and Hydrologic Response Unit (HRU) scales using SWAT-T. The HRU is the smallest spatial unit of the model, which lumps all similar land uses, soils, and slopes within a sub-basin. The SWAT-T model was parameterized for slope length, steepness and the empirical Universal Soil Erosion Equation support practice factor for three terrace segments. Data from 1993-2010 measured at the watershed outlet were used to evaluate the models for calibration and validation. Results of SWAT-T calibration showed good performance between measured and simulated erosion for the monthly time step, but poor performance for SWAT-T validation. This is probably because of large storms in spring 2002 that prevented planting, causing poorly simulated scheduling of actual field operations. To estimate terrace benefits on erosion, models were compared with and without terraces. Results showed that SWAT-T showed significant ~3% reduction in erosion (Pr <0.01) at the watershed scale and ~12% reduction in erosion at the HRU scale. Studies using the SWAT-T model indicated that the terraces have advantages to reduce erosion from terraced-agricultural watersheds. SWAT-T can be used in the evaluation of erosion to sustainably conserve the soil and water.

Keywords: Erosion, Modeling, Terraces, SWAT

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Authors: Emily Adams, Eddie Donaghy, David Henderson, Lauren Ng, Caroline Sanders, Rowena Stewart, Maria Wolters, Stewart Mercer

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Ongoing review abstract: Older People Experiencing Homelessness (OPEH) can have mental and physical indicators of aging 10–20 years earlier than the general population and experience premature mortality due to age-related chronic conditions. Emerging literature suggests digital interventions could positively impact PEH’s well-being. However, the increased reliance on digital delivery may also perpetuate digital inequalities for socially excluded groups, including PEH. The potential triple disadvantage of being older, homeless, and digitally excluded creates a uniquely problematic situation that warrants further research. This scoping review aims to investigate and synthesise the range and type of digital interventions available to OPEH and the organisations that support OPEH. The following databases were searched on 28th July 2023: Medline, Scopus, International Bibliography of the Social Sciences (IBSS)‎, Applied Social Sciences Index & Abstracts (ASSIA)‎, Association for Computing Machinery Digital Library (ACMDL) and Policy commons. A search strategy was developed in collaboration with an academic librarian. The presentation will include: An introduction to OPEH and digital exclusion Overview of the results of this review: OPEH usage of digital platforms Current digital interventions available The role of support organisations Current gaps in the evidence, future research and recommendations for policy and practice

Keywords: homeless, digital exclusion, aging, technology

Procedia PDF Downloads 47

Authors: Anthony Oppong Kyekyeku, Sussana Antwi-Boasiako, Emmanuel De-Graft Johnson Owusu Ansah

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In this observational study, the performance of a known conventional storage system was tested and evaluated for fitness for its intended purpose. The system has a scope extended for the storage of dry cocoa beans. System sensitivity, reproducibility and uncertainties are not known in details. This study discusses the system performance in the context of existing literature on factors that influence the quality of cocoa beans during storage. Controlled conditions were defined precisely for the system to give reliable base line within specific established procedures. Minitab® 17 and R statistical software (R-3.3.1) were used for the statistical analyses. The approach to the storage system testing was to observe and compare through laboratory test methods the quality of the cocoa beans samples before and after storage. The samples were kept in Kilner jars and the temperature of the storage environment controlled and monitored over a period of 408 days. Standard test methods use in international trade of cocoa such as the cut test analysis, moisture determination with Aqua boy KAM III model and bean count determination were used for quality assessment. The data analysis assumed the entire population as a sample in order to establish a reliable baseline to the data collected. The study concluded a statistically significant mean value at 95% Confidence Interval (CI) for the performance data analysed before and after storage for all variables observed. Correlational graphs showed a strong positive correlation for all variables investigated with the exception of All Other Defect (AOD). The weak relationship between the before and after data for AOD had an explained variability of 51.8% with the unexplained variability attributable to the uncontrolled condition of hidden infestation before storage. The current study concluded with a high-performance criterion for the storage system.

Keywords: benchmarking performance data, cocoa beans, hidden infestation, storage system validation

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Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan

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Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

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Authors: A. Ramachandra Reddy, V. Murugan, Prema Kumari

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Residual solvents in Pharmaceutical samples are monitored using gas chromatography with headspace (GC-HS). Based on current regulatory and compendial requirements, measuring the residual solvents are mandatory for all release testing of active pharmaceutical ingredients (API). Generally, isopropyl alcohol is used as the residual solvent in proline and tryptophan; methanol in cysteine monohydrate hydrochloride, glycine, methionine and serine; ethanol in glycine and lysine monohydrate; acetic acid in methionine. In order to have a single method for determining these residual solvents (isopropyl alcohol, ethanol, methanol and acetic acid) in all these 7 amino acids a sensitive and simple method was developed by using gas chromatography headspace technique with flame ionization detection. During development, no reproducibility, retention time variation and bad peak shape of acetic acid peaks were identified due to the reaction of acetic acid with the stationary phase (cyanopropyl dimethyl polysiloxane phase) of column and dissociation of acetic acid with water (if diluent) while applying temperature gradient. Therefore, dimethyl sulfoxide was used as diluent to avoid these issues. But most the methods published for acetic acid quantification by GC-HS uses derivatisation technique to protect acetic acid. As per compendia, risk-based approach was selected as appropriate to determine the degree and extent of the validation process to assure the fitness of the procedure. Therefore, Total error concept was selected to validate the analytical procedure. An accuracy profile of ±40% was selected for lower level (quantitation limit level) and for other levels ±30% with 95% confidence interval (risk profile 5%). The method was developed using DB-Waxetr column manufactured by Agilent contains 530 µm internal diameter, thickness: 2.0 µm, and length: 30 m. A constant flow of 6.0 mL/min. with constant make up mode of Helium gas was selected as a carrier gas. The present method is simple, rapid, and accurate, which is suitable for rapid analysis of isopropyl alcohol, ethanol, methanol and acetic acid in amino acids. The range of the method for isopropyl alcohol is 50ppm to 200ppm, ethanol is 50ppm to 3000ppm, methanol is 50ppm to 400ppm and acetic acid 100ppm to 400ppm, which covers the specification limits provided in European pharmacopeia. The accuracy profile and risk profile generated as part of validation were found to be satisfactory. Therefore, this method can be used for testing of residual solvents in amino acids drug substances.

Keywords: amino acid, head space, gas chromatography, total error

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: N. Alias, W. Z. W. Muhammad, M. N. M. Ibrahim, M. Mohamed, H. F. S. Saipol, U. N. Z. Ariffin, N. A. Zakaria, M. S. Z. Suardi

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This paper presents the performance comparison of some computation software for solving the boundary element method (BEM). BEM formulation is the numerical technique and high potential for solving the advance mathematical modeling to predict the production of oil well in arbitrarily shaped based on multiple leases reservoir. The limitation of data validation for ensuring that a program meets the accuracy of the mathematical modeling is considered as the research motivation of this paper. Thus, based on this limitation, there are three steps involved to validate the accuracy of the oil production simulation process. In the first step, identify the mathematical modeling based on partial differential equation (PDE) with Poisson-elliptic type to perform the BEM discretization. In the second step, implement the simulation of the 2D BEM discretization using COMSOL Multiphysic and MATLAB programming languages. In the last step, analyze the numerical performance indicators for both programming languages by using the validation of Fortran programming. The performance comparisons of numerical analysis are investigated in terms of percentage error, comparison graph and 2D visualization of pressure on oil production of multiple leases reservoir. According to the performance comparison, the structured programming in Fortran programming is the alternative software for implementing the accurate numerical simulation of BEM. As a conclusion, high-level language for numerical computation and numerical performance evaluation are satisfied to prove that Fortran is well suited for capturing the visualization of the production of oil well in arbitrarily shaped.

Keywords: performance comparison, 2D visualization, COMSOL multiphysic, MATLAB, Fortran, modelling and simulation, boundary element method, reservoir pressure

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Authors: Pascal Mwenge, Tumisang Seodigeng

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The combination of world population and the third industrial revolution led to high demand for fuels. On the other hand, the decrease of global fossil 8fuels deposits and the environmental air pollution caused by these fuels has compounded the challenges the world faces due to its need for energy. Therefore, new forms of environmentally friendly and renewable fuels such as biodiesel are needed. The primary analytical techniques for methanolysis yield monitoring have been chromatography and spectroscopy, these methods have been proven reliable but are more demanding, costly and do not provide real-time monitoring. In this work, the in situ monitoring of biodiesel from sunflower oil using FTIR (Fourier Transform Infrared) has been studied; the study was performed using EasyMax Mettler Toledo reactor equipped with a DiComp (Diamond) probe. The quantitative monitoring of methanolysis was performed by building a quantitative model with multivariate calibration using iC Quant module from iC IR 7.0 software. 15 samples of known concentrations were used for the modelling which were taken in duplicate for model calibration and cross-validation, data were pre-processed using mean centering and variance scale, spectrum math square root and solvent subtraction. These pre-processing methods improved the performance indexes from 7.98 to 0.0096, 11.2 to 3.41, 6.32 to 2.72, 0.9416 to 0.9999, RMSEC, RMSECV, RMSEP and R2Cum, respectively. The R² value of 1 (training), 0.9918 (test), 0.9946 (cross-validation) indicated the fitness of the model built. The model was tested against univariate model; small discrepancies were observed at low concentration due to unmodelled intermediates but were quite close at concentrations above 18%. The software eliminated the complexity of the Partial Least Square (PLS) chemometrics. It was concluded that the model obtained could be used to monitor methanol of sunflower oil at industrial and lab scale.

Keywords: biodiesel, calibration, chemometrics, methanolysis, multivariate analysis, transesterification, FTIR

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Authors: Kherbache Mehdi

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Within the framework of the validation of the Master in business administration marketing and sales in INSIM institute international in management Blida, we get the opportunity to do a professional internship in Sonelgaz Enterprise and a thesis. The thesis deals with the integration of social networking in the communication strategy of a company. The problematic is: How communicate with social network can be a solution for companies? The challenges stressed by this thesis were to suggest limits and recommendations to Sonelgaz Enterprise concerning social networks. The whole social networks represent more than a billion people as a potential target for the companies. Thanks to research and a qualitative approach, we have identified tree valid hypothesis. The first hypothesis allows confirming that using social networks cannot be ignored by any company in its communication strategy. However, the second hypothesis demonstrates that it’s necessary to prepare a strategy that integrates social networks in the communication plan of the company. The risk of this strategy is very limited because failure on social networks is not a restraint for the enterprise, social networking is not expensive and, a bad image which could result from it is not as important in the long-term. Furthermore, the return on investment is difficult to evaluate. Finally, the last hypothesis shows that firms establish a new relation between consumers and brands thanks to the proximity allowed by social networks. After the validation of the hypothesis, we suggested some recommendations to Sonelgaz Enterprise regarding the communication through social networks. Firstly, the company must use the interactivity of social network in order to have fruitful exchanges with the community. We also recommended having a strategy to treat negative comments. The company must also suggest delivering resources to the community thanks to a community manager, in order to have a good relation with the community. Furthermore, we advised using social networks to do business intelligence. Sonelgaz Enterprise can have some creative and interactive contents with some amazing applications on Facebook for example. Finally, we recommended to the company to be not intrusive with “fans” or “followers” and to be open to all the platforms: Twitter, Facebook, Linked-In for example.

Keywords: social network, buzz, communication, consumer, return on investment, internet users, web 2.0, Facebook, Twitter, interaction

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Authors: Ella Sèdé Maforikan

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Sustained water management requires quantitative information and the knowledge of spatiotemporal dynamics of hydrological system within the basin. This can be achieved through the research. Several studies have investigated both surface water and groundwater in Beterou catchment. However, there are few published papers on the application of the SWAT modeling in Beterou catchment. The objective of this study was to evaluate the performance of SWAT to simulate the water balance within the watershed. The inputs data consist of digital elevation model, land use maps, soil map, climatic data and discharge records. The model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI2) approach. The calibrated started from 1989 to 2006 with four years warming up period (1985-1988); and validation was from 2007 to 2020. The goodness of the model was assessed using five indices, i.e., Nash–Sutcliffe efficiency (NSE), the ratio of the root means square error to the standard deviation of measured data (RSR), percent bias (PBIAS), the coefficient of determination (R²), and Kling Gupta efficiency (KGE). Results showed that SWAT model successfully simulated river flow in Beterou catchment with NSE = 0.79, R2 = 0.80 and KGE= 0.83 for the calibration process against validation process that provides NSE = 0.78, R2 = 0.78 and KGE= 0.85 using site-based streamflow data. The relative error (PBIAS) ranges from -12.2% to 3.1%. The parameters runoff curve number (CN2), Moist Bulk Density (SOL_BD), Base Flow Alpha Factor (ALPHA_BF), and the available water capacity of the soil layer (SOL_AWC) were the most sensitive parameter. The study provides further research with uncertainty analysis and recommendations for model improvement and provision of an efficient means to improve rainfall and discharges measurement data.

Keywords: watershed, water balance, SWAT modeling, Beterou

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Authors: S. Hammoudeh, S. Ghuloum, A. Abdelhakam, A. AlMujalli, M. Opler, Y. Hani, A. Yehya, S. Mari, R. Elsherbiny, Z. Mahfoud, H. Al-Amin

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Introduction: Suicidal ideation and attempts are very common in patients with schizophrenia and still contributes to the high mortality in this population. The InterSePT Scale for Suicidal Thinking (ISST) is a validated tool used to assess suicidal ideation in patients with schizophrenia. This research aims to validate the Arabic version of the ISST among the Arabs residing in Qatar. Methods: Patients diagnosed with schizophrenia were recruited from the department of Psychiatry, Rumailah Hospital, Doha, Qatar. Healthy controls were recruited from the primary health care centers in Doha, Qatar. The validation procedures including professional and expert translation, pilot survey and back translation of the ISST were implemented. Diagnosis of schizophrenia was confirmed using the validated Arabic version of Mini International Neuropsychiatric Interview (MINI 6, module K) for schizophrenia. The gold standard was the module B on suicidality from MINI 6 also. This module was administered by a rater who was blinded to the results of ISST. Results: Our sample (n=199) was composed of 98 patients diagnosed with schizophrenia (age 36.03 ± 9.88 years; M/F is 2/1) and 101 healthy participants (age 35.01 ± 8.23 years; M/F is 1/2). Among patients with schizophrenia: 26.5% were married, 17.3% had a college degree, 28.6% were employed, 9% had committed suicide once, and 4.4% had more than 4 suicide attempts. Among the control group: 77.2% were married, 57.4% had a college degree, and 99% were employed. The mean score on the ISST was 2.36 ± 3.97 vs. 0.47 ± 1.44 for the schizophrenia and control groups, respectively. The overall Cronbach’s alpha was 0.91. Conclusions: This is the first study in the Arab world to validate the ISST in an Arabic-based population. The psychometric properties indicate that the Arabic version of the ISST is a valid tool to assess the severity of suicidal ideation in Arabic speaking patients diagnosed with schizophrenia.

Keywords: mental health, Qatar, schizophrenia, suicide

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Authors: Ahmad Ammar, Umar Khan Khattak, Muhammad Majid

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Empirically based lumped hydrologic models have an extensive track record of use for various watershed managements and flood related studies. This study focuses on the impacts of LULC change for 10 year period on the discharge in watershed using lumped model HEC-HMS. The Indus above Tarbela region acts as a source of the main flood events in the middle and lower portions of Indus because of the amount of rainfall and topographic setting of the region. The discharge pattern of the region is influenced by the LULC associated with it. In this study the Landsat TM images were used to do LULC analysis of the watershed. Satellite daily precipitation TRMM data was used as input rainfall. The input variables for model building in HEC-HMS were then calculated based on the GIS data collected and pre-processed in HEC-GeoHMS. SCS-CN was used as transform model, SCS unit hydrograph method was used as loss model and Muskingum was used as routing model. For discharge simulation years 2000 and 2010 were taken. HEC-HMS was calibrated for the year 2000 and then validated for 2010.The performance of the model was assessed through calibration and validation process and resulted R2=0.92 during calibration and validation. Relative Bias for the years 2000 was -9% and for2010 was -14%. The result shows that in 10 years the impact of LULC change on discharge has been negligible in the study area overall. One reason is that, the proportion of built-up area in the watershed, which is the main causative factor of change in discharge, is less than 1% of the total area. However, locally, the impact of development was found significant in built up area of Mansehra city. The analysis was done on Mansehra city sub-watershed with an area of about 16 km2 and has more than 13% built up area in 2010. The results showed that with an increase of 40% built-up area in the city from 2000 to 2010 the discharge values increased about 33 percent, indicating the impact of LULC change on discharge value.

Keywords: LULC change, HEC-HMS, Indus Above Tarbela, SCS-CN

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Authors: Mehmet Oren, Susan Pedersen, Sevket C. Cetin

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Despite the frequently criticized disadvantages of the traditional used paper and pencil assessment, it is the most frequently used method in our schools. Although assessments do an acceptable measurement, they are not capable of measuring all the aspects and the richness of learning and knowledge. Also, many assessments used in schools decontextualize the assessment from the learning, and they focus on learners’ standing on a particular topic but do not concentrate on how student learning changes over time. For these reasons, many scholars advocate that using simulations and games (S&G) as a tool for assessment has significant potentials to overcome the problems in traditionally used methods. S&G can benefit from the change in technology and provide a contextualized medium for assessment and teaching. Furthermore, S&G can serve as an instructional tool rather than a method to test students’ learning at a particular time point. To investigate the potentials of using educational games as an assessment and teaching tool, this study presents the implementation and the validation of an automated embedded assessment (AEA), which can constantly monitor student learning in the game and assess their performance without intervening their learning. The experiment was conducted on an undergraduate level engineering course (Digital Circuit Design) with 99 participant students over a period of five weeks in Spring 2016 school semester. The purpose of this research study is to examine if the proposed method of AEA is valid to assess student learning in a 3D Educational game and present the implementation steps. To address this question, this study inspects three aspects of the AEA for the validation. First, the evidence-centered design model was used to lay out the design and measurement steps of the assessment. Then, a confirmatory factor analysis was conducted to test if the assessment can measure the targeted latent constructs. Finally, the scores of the assessment were compared with an external measure (a validated test measuring student learning on digital circuit design) to evaluate the convergent validity of the assessment. The results of the confirmatory factor analysis showed that the fit of the model with three latent factors with one higher order factor was acceptable (RMSEA < 0.00, CFI =1, TLI=1.013, WRMR=0.390). All of the observed variables significantly loaded to the latent factors in the latent factor model. In the second analysis, a multiple regression analysis was used to test if the external measure significantly predicts students’ performance in the game. The results of the regression indicated the two predictors explained 36.3% of the variance (R2=.36, F(2,96)=27.42.56, p<.00). It was found that students’ posttest scores significantly predicted game performance (β = .60, p < .000). The statistical results of the analyses show that the AEA can distinctly measure three major components of the digital circuit design course. It was aimed that this study can help researchers understand how to design an AEA, and showcase an implementation by providing an example methodology to validate this type of assessment.

Keywords: educational video games, automated embedded assessment, assessment validation, game-based assessment, assessment design

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Mikiyas Adugna

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Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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Authors: Catarina Belchior, Catarina Martins, Sara Mendes, Ana Rita S. Valente, Elsa Marta Soares

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Introduction: The negative feelings and attitudes that a person who stutters can develop are extremely relevant when considering assessment and intervention in Speech and Language Therapy. This relates to the fact that the person who stutters can experience feelings such as shame, fear and negative beliefs when communicating. Considering the complexity and importance of integrating diverse aspects in stuttering intervention, it is central to identify those emotions as early as possible. Therefore, this research aimed to achieve the translation, adaptation to European Portuguese and to analyze the content validation of the Preschooler Awareness Stuttering Survey (Abbiati, Guitar & Hutchins, 2015), an instrument that allows the assessment of the impact of stuttering on preschool children who stutter considering feelings and attitudes. Methodology: Cross-sectional descriptive qualitative research. The following methodological procedures were followed: translation, back-translation, panel of experts and pilot study. This abstract describes the results of the first three phases of this process. The translation was accomplished by two Speech Language Therapists (SLT). Both professionals have more than five years of experience and are users of English language. One of them has a broad experience in the field of stuttering. Back-translation was conducted by two bilingual individuals without experience in health or any knowledge about the instrument. The panel of experts was composed by 3 different SLT, experts in the field of stuttering. Results and Discussion: In the translation and back-translation process it was possible to verify differences in semantic and idiomatic equivalences of several concepts and expressions, as well as the need to include new information to enhance the understanding of the application of the instrument. The meeting between the two translators and the researchers allowed the achievement of a consensus version that was used in back-translation. Considering adaptation and content validation, the main change made by the experts was the conceptual equivalence of the questions and answers of the instrument's sheets. Considering that in the translated consensus version the questions began with various nouns such as 'is' or 'the cow' and that the answers did not contain the adverb 'much' as in the original instrument, the panel agreed that it would be more appropriate if the questions all started with 'how' and that all the answers should present the adverb 'much'. This decision was made to ensure that the translate instrument would be similar to the original and so that the results obtained could be comparable between the original and the translated instrument. There was also elaborated one semantic equivalence between concepts. The panel of experts found that all other items and specificities of the instrument were adequate, concluding the adequacy of the instrument considering its objectives and its intended target population. Conclusion: This research aspires to diversify the existing validated resources in this scope, adding a new instrument that allows the assessment of preschool children who stutter. Consequently, it is hoped that this instrument will provide a real and reliable assessment that can lead to an appropriate therapeutic intervention according to the characteristics and needs of each child.

Keywords: stuttering, assessment, feelings and attitudes, speech language therapy

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Authors: Mindaugas Liaudanskas, Darius Kviklys, Kristina Zymonė, Raimondas Raudonis, Jonas Viškelis, Norbertas Uselis, Pranas Viškelis, Valdimaras Janulis

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Apples are among the most commonly consumed fruits in the world. Based on data from the year 2014, approximately 84.63 million tons of apples are grown per annum. Apples are widely used in food industry to produce various products and drinks (juice, wine, and cider); they are also used unprocessed. Apples in human diet are an important source of different groups of biological active compounds that can positively contribute to the prevention of various diseases. They are a source of various biologically active substances – especially vitamins, organic acids, micro- and macro-elements, pectins, and phenolic, triterpenic, and other compounds. Triterpenic compounds, which are characterized by versatile biological activity, are the biologically active compounds found in apples that are among the most promising and most significant for human health. A specific analytical procedure including sample preparation and High Performance Liquid Chromatography (HPLC) analysis was developed, optimized, and validated for the detection of triterpenic compounds in the samples of different apples, their peels, and flesh from widespread apple cultivars 'Aldas', 'Auksis', 'Connel Red', 'Ligol', 'Lodel', and 'Rajka' grown in Lithuanian climatic conditions. The conditions for triterpenic compound extraction were optimized: the solvent of the extraction was 100% (v/v) acetone, and the extraction was performed in an ultrasound bath for 10 min. Isocratic elution (the eluents ratio being 88% (solvent A) and 12% (solvent B)) for a rapid separation of triterpenic compounds was performed. The validation of the methodology was performed on the basis of the ICH recommendations. The following characteristics of validation were evaluated: the selectivity of the method (specificity), precision, the detection and quantitation limits of the analytes, and linearity. The obtained parameters values confirm suitability of methodology to perform analysis of triterpenic compounds. Using the optimised and validated HPLC technique, four triterpenic compounds were separated and identified, and their specificity was confirmed. These compounds were corosolic acid, betulinic acid, oleanolic acid, and ursolic acid. Ursolic acid was the dominant compound in all the tested apple samples. The detected amount of betulinic acid was the lowest of all the identified triterpenic compounds. The greatest amounts of triterpenic compounds were detected in whole apple and apple peel samples of the 'Lodel' cultivar, and thus apples and apple extracts of this cultivar are potentially valuable for use in medical practice, for the prevention of various diseases, for adjunct therapy, for the isolation of individual compounds with a specific biological effect, and for the development and production of dietary supplements and functional food enriched in biologically active compounds. Acknowledgements. This work was supported by a grant from the Research Council of Lithuania, project No. MIP-17-8.

Keywords: apples, HPLC, triterpenic compounds, validation

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Authors: Konrad Pietrykowski, Michał Gęca, Michał Bialy

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The paper presents the results of the crankshaft strength simulation. The crankshaft was taken from the opposed piston engine. Calculations were made using finite element method (FEM) in Abaqus software. This program allows to perform strength tests of individual machine parts as well as their assemblies. The crankshaft that was used in the calculations will be used in the two-stroke aviation research aircraft engine. The assumptions for the calculations were obtained from the AVL Boost software, from one-dimensional engine cycle model and from the multibody model using the method developed in the MSC Adams software. The research engine will be equipped with 3 combustion chambers and two crankshafts. In order to shorten the calculation time, only one crankcase analysis was performed. The cut of the shaft has been selected with the greatest forces resulting from the engine operation. Calculations were made for two cases. For maximum piston force when maximum bending load occurs and for the maximum torque. Cast iron material was adopted. For this material, Poisson's number, density, and Young's modulus were determined. The computational grid contained of 1,977,473 Tet elements. This type of elements was chosen because of the complex design of the crankshaft. Results are presented in the form of stress distributions maps and displacements on the surface and inside the geometry of the shaft. The results show the places of tension stresses, however, no stresses are exceeded at any place. The shaft can thus be applied to the engine in its present form. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK 'PZL-KALISZ’ S.A. and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: aircraft diesel engine, crankshaft, finite element method, two-stroke engine

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Authors: Pinna Beatrice., Laini Alex, Negro Giovanni, Burgazzi Gemma, Viaroli Pierluigi, Vezza Paolo

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Habitat models rarely consider macroinvertebrates as ecological targets in rivers. Available approaches mainly focus on single macroinvertebrate species, not addressing the ecological needs and functionality of the entire community. This research aimed to provide an approach to model the habitat of the macroinvertebrate community. The approach is based on the recently developed Flow-T index, together with a Random Forest (RF) regression, which is employed to apply the Flow-T index at the meso-habitat scale. Using different datasets gathered from both field data collection and 2D hydrodynamic simulations, the model has been calibrated in the Trebbia river (2019 campaign), and then validated in the Trebbia, Taro, and Enza rivers (2020 campaign). The three rivers are characterized by a braiding morphology, gravel riverbeds, and summer low flows. The RF model selected 12 mesohabitat descriptors as important for the macroinvertebrate community. These descriptors belong to different frequency classes of water depth, flow velocity, substrate grain size, and connectivity to the main river channel. The cross-validation R² coefficient (R²𝒸ᵥ) of the training dataset is 0.71 for the Trebbia River (2019), whereas the R² coefficient for the validation datasets (Trebbia, Taro, and Enza Rivers 2020) is 0.63. The agreement between the simulated results and the experimental data shows sufficient accuracy and reliability. The outcomes of the study reveal that the model can identify the ecological response of the macroinvertebrate community to possible flow regime alterations and to possible river morphological modifications. Lastly, the proposed approach allows extending the MesoHABSIM methodology, widely used for the fish habitat assessment, to a different ecological target community. Further applications of the approach can be related to flow design in both perennial and non-perennial rivers, including river reaches in which fish fauna is absent.

Keywords: ecological flows, macroinvertebrate community, mesohabitat, river habitat modeling

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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Quantitative structure-retention relationship (QSRR) analysis was used to predict the chromatographic behavior of s-triazine derivatives by using theoretical descriptors computed from the chemical structure. Fundamental basis of the reported investigation is to relate molecular topological descriptors with chromatographic behavior of s-triazine derivatives obtained by reversed-phase (RP) thin layer chromatography (TLC) on silica gel impregnated with paraffin oil and applied ethanol-water (φ = 0.5-0.8; v/v). Retention parameter (RM0) of 14 investigated s-triazine derivatives was used as dependent variable while simple connectivity index different orders were used as independent variables. The best QSRR model for predicting RM0 value was obtained with simple third order connectivity index (3χ) in the second-degree polynomial equation. Numerical values of the correlation coefficient (r=0.915), Fisher's value (F=28.34) and root mean square error (RMSE = 0.36) indicate that model is statistically significant. In order to test the predictive power of the QSRR model leave-one-out cross-validation technique has been applied. The parameters of the internal cross-validation analysis (r2CV=0.79, r2adj=0.81, PRESS=1.89) reflect the high predictive ability of the generated model and it confirms that can be used to predict RM0 value. Multivariate classification technique, hierarchical cluster analysis (HCA), has been applied in order to group molecules according to their molecular connectivity indices. HCA is a descriptive statistical method and it is the most frequently used for important area of data processing such is classification. The HCA performed on simple molecular connectivity indices obtained from the 2D structure of investigated s-triazine compounds resulted in two main clusters in which compounds molecules were grouped according to the number of atoms in the molecule. This is in agreement with the fact that these descriptors were calculated on the basis of the number of atoms in the molecule of the investigated s-triazine derivatives.

Keywords: s-triazines, QSRR, chemometrics, chromatography, molecular descriptors

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