Search results for: curve fitting

Authors: Ricky Saputra, Rashmi Walvekar, Mohammad Khalid, Kaveh Shahbaz, Suganti Ramarad

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This particular study of interest aims to study the effect of coupling ultrasonic treatment with eutectic solvents in devulcanization process of waste rubber tyre. Specifically, three different types of Deep Eutectic Solvents (DES) were utilized, namely ChCl:Urea (1:2), ChCl:ZnCl₂ (1:2) and ZnCl₂:urea (2:7) in which their physicochemical properties were analysed and proven to have permissible water content that is less than 3.0 wt%, degradation temperature below 200ᵒC and freezing point below 60ᵒC. The mass ratio of rubber to DES was varied from 1:20-1:40, sonicated for 1 hour at 37 kHz and heated at variable time of 5-30 min at 180ᵒC. Energy dispersive x-rays (EDX) results revealed that the first two DESs give the highest degree of sulphur removal at 74.44 and 76.69% respectively with optimum heating time at 15 minutes whereby if prolonged, reformation of crosslink network would be experienced. Such is supported by the evidence shown by both FTIR and FESEM results where di-sulfide peak reappears at 30 minutes and morphological structures from 15 to 30 minutes change from smooth with high voidage to rigid with low voidage respectively. Furthermore, TGA curve reveals similar phenomena whereby at 15 minutes thermal decomposition temperature is at the lowest due to the decrease of molecular weight as a result of sulphur removal but increases back at 30 minutes. Type of bond change was also analysed whereby it was found that only di-sulphide bond was cleaved and which indicates partial-devulcanization. Overall, the results show that DES has a great potential to be used as devulcanizing solvent.

Keywords: crosslink network, devulcanization, eutectic solvents, reformation, ultrasonic

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Authors: Bjorn Kierulf, Arun Chundru

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Over the past decade, collegiate rocketry teams have emerged across the country with various goals: space, liquid-fueled flight, etc. A critical piece of the development of knowledge within a club is the use of so-called "sounding rockets," whose goal is to take in-flight measurements that inform future rocket design. Common measurements include acceleration from inertial measurement units (IMU's), and altitude from barometers. With a properly tuned filter, these measurements can be used to find velocity, but are susceptible to noise, offset, and filter settings. Instead, velocity can be measured more directly and more instantaneously using a pitot tube, which operates by measuring the stagnation pressure. At supersonic speeds, an additional thermodynamic property is necessary to constrain the upstream state. One possibility is the stagnation temperature, measured by a thermocouple in the pitot tube. The routing of the pitot tube from the nosecone tip down to a pressure transducer is complicated by the nosecone's structure. Commercial-off-the-shelf (COTS) nosecones come with a removable metal tip (without a pitot tube). This provides the opportunity to make custom tips with integrated measurement systems without making the nosecone from scratch. The main design constraint is how the nosecone tip is held down onto the nosecone, using the tension in a threaded rod anchored to a bulkhead below. Because the threaded rod connects into a threaded hole in the center of the nosecone tip, the pitot tube follows a winding path, and the pressure fitting is off-center. Two designs will be presented in the paper, one with a curved pitot tube and a coaxial design that eliminates the need for the winding path by routing pressure through a structural tube. Additionally, three manufacturing methods will be presented for these designs: bound powder filament metal 3D printing, stereo-lithography (SLA) 3D printing, and traditional machining. These will employ three different materials, copper, steel, and proprietary resin. These manufacturing methods and materials are relatively low cost, thus accessible to student researchers. These designs and materials cover multiple use cases, based on how fast the sounding rocket is expected to travel and how important heating effects are - to measure and to avoid melting. This paper will include drawings showing key features and an overview of the design changes necessitated by the manufacture. It will also include a look at the successful use of these nosecone tips and the data they have gathered to date.

Keywords: additive manufacturing, machining, pitot tube, sounding rocketry

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Authors: Darn H. Hsiao, Zhu-Yun Zheng

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Since Taiwan is located between the Eurasian and Filipino plates and earthquakes often thus occur. The coastal plains in western Taiwan are alluvial plains, and the soils of the alluvium are mostly from the Lao-Shan belt in the central mountainous area of ​​southern Taiwan. It could come mostly from sand/shale and slate. The previous investigation found that the soils in the Kaohsiung area of ​​southern Taiwan are mainly composed of slate, shale, quartz, low-plastic clay, silt, silty sand and so on. It can also be found from the past earthquakes that the soil in Kaohsiung is highly susceptible to soil subsidence due to liquefaction. Insufficient bearing capacity of building will cause soil liquefaction disasters. In this study, the boring drilling data from nine districts among the Love River Basin in the city center, and some factors affecting liquefaction include the content of fines (FC), standard penetration test N value (SPT N), the thickness of clay layer near ground-surface, and the thickness of possible liquefied soil were further discussed for liquefaction potential as well as groundwater level. The results show that the liquefaction potential is higher in the areas near the riverside, the backfill area, and the west area of ​​the study area. This paper also uses the old paleo-geological map, soil particle distribution curve, compared with LPI map calculated from the analysis results. After all the parameters finally were studied for five sub zones in the Love River Basin by maximum-minimum method, it is found that both of standard penetration test N value and the thickness of the clay layer will be most influential.

Keywords: liquefaction, western Taiwan, liquefaction potential map, high liquefaction potential areas

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Authors: Giorgio Visentin, Alexei A. Buchachenko

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Recent proposals to use Yb dimer as an optical clock and as a sensor for non-Newtonian gravity imply the knowledge of its interaction potential. Here, the ground-state Born-Oppenheimer Yb₂ potential energy curve is represented by a semi-analytical function, consisting of short- and long-range contributions. For the former, the systematic ab initio all-electron exact 2-component scalar-relativistic CCSD(T) calculations are carried out. Special care is taken to saturate diffuse basis set component with the atom- and bond-centered primitives and reach the complete basis set limit through n = D, T, Q sequence of the correlation-consistent polarized n-zeta basis sets. Similar approaches are used to the long-range dipole and quadrupole dispersion terms by implementing the CCSD(3) polarization propagator method for dynamic polarizabilities. Dispersion coefficients are then computed through Casimir-Polder integration. The semiclassical constraint on the number of the bound vibrational levels known for the ¹⁷⁴Yb isotope is used to scale the potential function. The scaling, based on the most accurate ab initio results, bounds the interaction energy of two Yb atoms within the narrow 734 ± 4 cm⁻¹ range, in reasonable agreement with the previous ab initio-based estimations. The resulting potentials can be used as the reference for more sophisticated models that go beyond the Born-Oppenheimer approximation and provide the means of their uncertainty estimations. The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: ab initio coupled cluster methods, interaction potential, semi-analytical function, ytterbium dimer

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Authors: Adrien Pyskir, Manuel Collet, Zoran Dimitrijevic, Claude-Henri Lamarque

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During the last decades, great efforts have been made to reduce acoustic and vibrational disturbances in transportations, as it has become a key feature for comfort. Today, isolation and design have neutralized most of the troublesome vibrations, so that cars are quieter and more comfortable than ever. However, some problems remain unsolved, in particular concerning low-frequency isolation and the frequency-dependent stiffening of materials like rubber. To sum it up, a balance has to be found between a high static stiffness to sustain the vibration source’s mass, and low dynamic stiffness, as wideband as possible. Systems meeting these criteria are yet to be designed. We thus investigated solutions inspired by metamaterials to control efficiently low-frequency wave propagation. Structures exhibiting a negative Poisson ratio, also called auxetic structures, are known to influence the propagation of waves through beaming or damping. However, their stiffness can be quite peculiar as well, as they can present regions of zero stiffness on the stress-strain curve for compression. In addition, auxetic materials can be easily adapted in many ways, inducing great tuning potential. Using finite element software COMSOL Multiphysics, a resonant design has been tested through statics and dynamics simulations. These results are compared to experimental results. In particular, the bandgaps featured by these structures are analyzed as a function of design parameters. Great stiffness properties can be observed, including low-frequency dynamic stiffness loss and broadband transmission loss. Such features are very promising for practical isolation purpose, and we hope to adopt this kind of metamaterial into an effective industrial damper.

Keywords: auxetics, metamaterials, structural dynamics, vibration isolation

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Authors: Luciana C. Ramos, Leandro J. Sousa, Antônio Ferreira da Silva, Valéria Gomes Oliveira Falcão, Suzana T. Cunha Lima

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The commercial production of biodiesel using microalgae demands a high-energy input for harvesting biomass, making production economically unfeasible. Methods currently used involve mechanical, chemical, and biological procedures. In this work, a flocculation system is presented as a cost and energy effective process to increase biomass production of Phaeodactylum tricornutum. This diatom is the only species of the genus that present fast growth and lipid accumulation ability that are of great interest for biofuel production. The algae, selected from the Bank of Microalgae, Institute of Biology, Federal University of Bahia (Brazil), have been bred in tubular reactor with photoperiod of 12 h (clear/dark), providing luminance of about 35 μmol photons m^-2s^-1, and temperature of 22 °C. The medium used for growing cells was the Conway medium, with addition of silica. The seaweed growth curve was accompanied by cell count in Neubauer camera and by optical density in spectrophotometer, at 680 nm. The precipitation occurred at the end of the stationary phase of growth, 21 days after inoculation, using two methods: centrifugation at 5000 rpm for 5 min, and electro-flocculation at 19 EPD and 95 W. After precipitation, cells were frozen at -20 °C and, subsequently, lyophilized. Biomass obtained by electro-flocculation was approximately four times greater than the one achieved by centrifugation. The benefits of this method are that no addition of chemical flocculants is necessary and similar cultivation conditions can be used for the biodiesel production and pharmacological purposes. The results may contribute to improve biodiesel production costs using marine microalgae.

Keywords: biomass, diatom, flocculation, microalgae

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Keerthie Dissanayake, Chandrika Jayasinghe, Priyani Wanigasekara, Jayampathy Dissanayake, Ajith Sominanda

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The routine use of Disease Activity Score-28 (DAS28) to assess the disease activity in rheumatoid arthritis (RA) is limited due to its dependency on laboratory investigations and the complex calculations involved. In contrast, the clinical disease activity index (CDAI) is simple to calculate, which makes the "treat to target" strategy for the management of RA more practical. We aimed to assess the validity of CDAI compared to DAS28 in RA patients in Sri Lanka. A total of 103 newly diagnosed RA patients were recruited, and their disease activity was calculated using DAS 28 and CDAI during the first visit to the clinic (0 months) and re-assessed at 4 and 9 months of the follow-up visits. The validity of the CDAI, compared to DAS 28, was evaluated. Patients had a female preponderance (6:1) and a short symptom duration (mean = 6.33 months). The construct validity of CDAI, as assessed by Cronbach's α test, was 0.868. Convergent validity was assessed by correlation and Kappa statistics. Strong positive correlations were observed between CDAI and DAS 28 at the baseline (0 months), 4, and 9 months of evaluation (Spearman's r = 0.9357, 0.9354, 0.9106, respectively). Moderate-good inter-rater agreements between the DAS-28 and CDAI were observed (Weighted kappa of 0.660, 0.519, and 0.741 at 0, 4, and 9 months respectively). Discriminant validity, as assessed by ROC curves at 0, 4th, and 9th months of the evaluation, showed the area under the curve (AUC) of 0.958, 0.985, and 0.914, respectively. The suggested cut-off points for different CDAI disease activity categories according to ROC curves were ≤ 2 (Remission), >2 to ≤ 5 (low), >5 to ≤ 18 (moderate), > 18 (high). These findings indicate that the CDAI has good concordance with DAS 28 in assessing the disease activity in RA patients in this study sample.

Keywords: rheumatoid arthritis, CDAI, disease activity, Sri Lanka, validation

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Authors: Nathen A. Spitz, Dennis Martin Kivlighan III, Arwa Aburizik

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Background and Purpose: Presently, there is a paucity of naturalistic studies that directly compare the effectiveness of psychotherapy versus concurrent psychotherapy and psychiatric care for the treatment of depression and anxiety in cancer patients. Informed by previous clinical trials examining the efficacy of concurrent approaches, this study sought to test the hypothesis that a combined approach would result in the greatest reduction of depression and anxiety symptoms. Methods: Data for this study consisted of 433 adult cancer patients, with 252 receiving only psychotherapy and 181 receiving concurrent psychotherapy and psychiatric care at the University of Iowa Hospitals and Clinics. Longitudinal PHQ9 and GAD7 data were analyzed between both groups using latent growth curve analyses. Results: After controlling for treatment length and provider effects, results indicated that concurrent care was more effective than psychotherapy alone for depressive symptoms (γ₁₂ = -0.12, p = .037). Specifically, the simple slope for concurrent care was -0.25 (p = .022), and the simple slope for psychotherapy alone was -0.13 (p = .006), suggesting that patients receiving concurrent care experienced a greater reduction in depressive symptoms compared to patients receiving psychotherapy alone. In contrast, there were no significant differences between psychotherapy alone and concurrent psychotherapy and psychiatric care in the reduction of anxious symptoms. Conclusions: Overall, as both psychotherapy and psychiatric care may address unique aspects of mental health conditions, in addition to potentially providing synergetic support to each other, a combinatorial approach to mental healthcare for cancer patients may improve outcomes.

Keywords: psychiatry, psychology, psycho-oncology, combined care, psychotherapy, behavioral psychology

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Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

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The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

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Authors: Fatima Achouri, Kaddour Chouicha, Abdelwahab Khatir

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It is clear that concrete of quality must be made with selected materials chosen in optimum proportions that remain after implementation, a minimum of voids in the material produced. The different methods of formulations what we use, are based for the most part on a granular curve which describes an ‘optimal granularity’. Many authors have engaged in fundamental research on granular arrangements. A comparison of mathematical models reproducing these granular arrangements with experimental measurements of compactness have to verify that the minimum porosity P according to the following extent granular exactly a power law. So the best compactness in the finite medium are obtained with power laws, such as Furnas, Fuller or Talbot, each preferring a particular setting between 0.20 and 0.50. These considerations converge on the assumption that the optimal granularity Caquot approximates by a power law. By analogy, it can then be analyzed as a granular structure of fractal-type since the properties that characterize the internal similarity fractal objects are reflected also by a power law. Optimized mixtures may be described as a series of installments falling granular stuff to better the tank on a regular hierarchical distribution which would give at different scales, by cascading effects, the same structure to the mix. Likely this model may be appropriate for the entire extent of the size distribution of the components, since the cement particles (and silica fume) correctly deflocculated, micrometric dimensions, to chippings sometimes several tens of millimeters. As part of this research, the aim is to give an illustration of the application of fractal analysis to characterize the granular concrete mixtures optimized for a so-called fractal dimension where different concretes were studying that we proved a fractal structure of their granular mixtures regardless of the method of formulation or the type of concrete.

Keywords: concrete formulation, fractal character, granular packing, method of formulation

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Authors: Majid Saaly, Shahriar Tavousi Tafreshi, Mehdi Nazari Afshar

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Most reinforced concrete structures are designed only under heavy loads have large transverse reinforcement spacing values, and therefore suffer severe failure after intense ground movements. The main goal of this paper is to compare the shear- and axial failure of concrete bending frames available in Tehran using incremental dynamic analysis under near- and far-field records. For this purpose, IDA analyses of 5, 10, and 15-story concrete structures were done under seven far-fault records and five near-faults records. The results show that in two-dimensional models of short-rise, mid-rise and high-rise reinforced concrete frames located on Type-3 soil, increasing the distance of the transverse reinforcement can increase the maximum inter-story drift ratio values up to 37%. According to the existing results on 5, 10, and 15-story reinforced concrete models located on Type-3 soil, records with characteristics such as fling-step and directivity create maximum drift values between floors more than far-fault earthquakes. The results indicated that in the case of seismic excitation modes under earthquake encompassing directivity or fling-step, the probability values of failure and failure possibility increasing rate values are much smaller than the corresponding values of far-fault earthquakes. However, in near-fault frame records, the probability of exceedance occurs at lower seismic intensities compared to far-fault records.

Keywords: IDA, failure curve, directivity, maximum floor drift, fling step, evaluating probable bending of frames, near-field and far-field earthquake records

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Authors: Wesam Darawsheh

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Purpose: There is an absence of studies directed to evaluate the effectiveness of Community Based Rehabilitation (CBR) programs in Jordan. This research study is aimed at investigating the effectiveness of the services of CBR programmes in Jordan. Method: A questionnaire anonymized survey was carried out with forty-seven participants (stakeholders and volunteers) from four CBR centres in Jordan. It comprised eighteen questions that collected both qualitative and quantitative data with both closed- and open-ended questions. The survey assessed participants’ knowledge of CBR and perception of the effectiveness of services provided. The quantitative data were analyzed using SPSS Version 22.0 (2016, IBM Corporation New York). Qualitative data were analyzed through thematic content and analysis and open coding to identify emergent themes. Results: The ROC curve revealed that the AUC for questions of the survey to be (AUC=0.846) which indicated a good specificity and sensitivity of the questions of the survey. The MANOVA revealed insignificant results in the effect of the CBR site (p= 0.157), and the level of education of participants (p=0.549), on the perception of the effectiveness of CBR services. There were insignificant differences between the scores of PWDs and volunteers (p=0.781). 40.4% evaluated the effectiveness of CBR services to be low. This mainly stemmed out from the lack of efforts of the CBR programmes to raise the knowledge of the local community about CBR, disability and the role toward PWDs. Conclusions: A speculation for priorities of CBR programmes in Jordan was offered where efforts need to be directed at promoting livelihood and the empowerment components, in order to actualize the main three principles of CBR mainly by promoting multispectral collaboration as a way of operation.

Keywords: community based rehabilitation (CBR), people with disabilities (PWDS), CBR centres, rehabilitation services, Jordan, mixed-methods, evaluative study

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Authors: Paul E. Jose

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A new self-report measure named the General Emotion Regulation Measure (GERM) assesses four key goals for experiencing broad valenced groups of emotions: 1) trying to experience positive emotions (e.g., joy, pride, liking a person); 2) trying to avoid experiencing positive emotions; 3) trying to experience negative emotions (e.g., anger, anxiety, contempt); and 4) trying to avoid experiencing negative emotions. Although individual differences in GERM motives have been identified, evidence of validity with common mood outcomes is lacking. In the present study, whether GERM motives predict self-reported subjective happiness and depressive symptoms (CES-D) was tested with a community sample of 833 young adults. It was predicted that the GERM motive of trying to experience positive emotions would positively predict subjective happiness, and analogously trying to experience negative emotions would predict depressive symptoms. An initial path model was constructed in which the four GERM motives predicted both subjective happiness and depressive symptoms. The fully saturated model included three non-significant paths, which were subsequently pruned, and a good fitting model was obtained (CFI = 1.00; RMR = .007). Two GERM motives significantly predicted subjective happiness: 1) trying to experience positive emotions ( = .38, p < .001) and 2) trying to avoid experiencing positive emotions ( = -.48, p <.001). Thus, individuals who reported high levels of trying to experience positive emotions reported high levels of happiness, and individuals who reported low levels of trying to avoid experiencing positive emotions also reported high levels of happiness. Three GERM motives significantly predicted depressive symptoms: 1) trying to avoid experiencing positive emotions ( = .20, p <.001); 2) trying to experience negative emotions ( = .15, p <.001); and 3) trying to experience positive emotions (= -.07, p <.001). In agreement with predictions, trying to experience positive emotions was positively associated with subjective happiness and trying to experience negative emotions was positively associated with depressive symptoms. In essence, these two valenced mood states seem to be sustained by trying to experience similarly valenced emotions. However, the three other significant paths in the model indicated that emotional motives play a complicated role in supporting both positive and negative mood states. For subjective happiness, the GERM motive of not trying to avoid positive emotions, i.e., not avoiding happiness, was also a strong predictor of happiness. Thus, people who report being the happiest are those individuals who not only strive to experience positive emotions but also are not ambivalent about them. The pattern for depressive symptoms was more nuanced. Individuals who reported higher depressive symptoms also reported higher levels of avoiding positive emotions and trying to experience negative emotions. The strongest predictor for depressed mood was avoiding positive emotions, which would suggest that happiness aversion or fear of happiness is an important motive for dysphoric people. Future work should determine whether these patterns of association are similar among clinically depressed people, and longitudinal data are needed to determine temporal relationships between motives and mood states.

Keywords: emotions motives, depression, subjective happiness, path model

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Authors: Sangeeta Pilkhwal Sah, C. S. Mathela, Kanwaljit Chopra

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Valeriana wallichii DC, an ayurvedic traditional medicine, popularly named as Indian valerian exist as three chemotypes. GC-MS analysis of V. wallichii essential oil in present study showed maaliol as the major constituent followed by the presence of β-gurjunene, acoradiene, guaiol and α-santalene. The results thus confirmed it to be a maaliol chemotype. Further, the antidepressant-like effect of root essential oil (10, 20 and 40 mg/kg p.o.) was investigated in both acute and chronic treatment study using forced swim test in mice. Single administration of different doses produced an inverted U shaped curve and significantly inhibited the immobility period (39.7% and 58%) at doses 10 and 40 mg/kg respectively. Standard drug imipramine significantly decreased immobility period (59.8%). None of the doses altered locomotor activity except a significant decrease of 44.9% was observed with 40 mg/kg (p < 0.05). Similarly, daily administration of essential oil for 14 days produced a dose dependent effect with significantly reduced immobility period (70.9%) at 40 mg/kg dose only whereas imipramine produced 86% decrease (p < 0.05). The neurotransmitter levels in mouse brain were estimated on day 14 after the behavioral study. Significant increase in the level of norepinephrine (10%) and dopamine (23%) (p < 0.05) was found at 40 mg/kg dose, while no change was observed at 10 and 20 mg/kg doses. The antidepressant-like effect of essential oil (40 mg/kg) was prevented by pretreatment of mice with L-arginine (750 mg/kg i.p.) and sildenafil (5 mg/kg i.p). On the contrary, pretreatment of mice with L-NAME (10 mg/kg i.p.) or methylene blue (10 mg/kg i.p.) potentiated the antidepressant action of essential oil (20 mg/kg). The findings thus demonstrated that nitric oxide pathway is involved in mediating antidepressant like effect of essential oil from this chemotype.

Keywords: Valeriana wallichii DC chemotype, essential oil, forced swim test, nitric oxide modulators, neurotransmitters

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Authors: Robin Molinier

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Industrial symbiosis (I.S) deals with both substitution synergies (exchange of waste materials, fatal energy and utilities as resources for production) and infrastructure/service sharing synergies. The latter is based on the intensification of use of an asset and thus requires to balance capital costs increments with snowball effects (network externalities) for its implementation. Initial investors must specify ex-ante arrangements (cost sharing and pricing schedule) to commit toward investments in capacities and transactions. Our model investigate the decision of 2 actors trying to choose cooperatively a level of infrastructure capacity oversizing to set a plug-and-play offer to a potential entrant whose capacity requirement is randomly distributed while satisficing their own requirements. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period. The entrant’s willingness-to-pay for the access to the infrastructure is dependent upon its standalone cost and the capacity gap that it must complete in case the available capacity is insufficient ex-post (the complement cost). Since initial capacity choices are driven by ex-ante (expected) yield extractible from the entrant we derive the expected complement cost function which helps us defining the investors’ objective function. We first show that this curve is decreasing and convex in the capacity increments and that it is shaped by the distribution function of the potential entrant’s requirements. We then derive the general form of solutions and solve the model for uniform and triangular distributions. Depending on requirements volumes and cost assumptions different equilibria occurs. We finally analyze the effect of a per-unit subsidy a public actor would apply to foster such sharing synergies.

Keywords: capacity, cooperation, industrial symbiosis, pricing

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Authors: Mukunda Upreti, Jill Storry, Rafael Björk, Emilie Louvet, Johan Normark, Sven Bergström

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Borrelia duttonii and most other relapsing fever species are Gram-negative bacteria which cause a blood borne infection characterized by the binding of bacterium to erythrocytes. The bacteria associate with two or more erythrocytes to form clusters of cells into rosettes. Rosetting is a major virulence factor and the mechanism is believed to facilitate persistence of bacteria in the circulatory system and the avoidance of host immune cells through masking or steric hindrance effects. However, the molecular mechanisms of rosette formation are still poorly understood. This study aims at determining the molecules involved in the rosette formation phenomenon. Fractionated serum, using different affinity purification methods, was investigated as a rosetting agent and IgG and at least one other serum components were needed for rosettes to form. An IgG titration curve demonstrated that IgG alone is not enough to restore rosette formation level to the level whole serum gives. IgG hydrolysis by IdeS ( Immunoglobulin G-degrading enzyme of Streptococcus pyogenes) and deglycosylation using N-Glycanase proved that the whole IgG molecule regardless of saccharide moieties is critical for Borrelia induced rosetting. Complement components C3 and C4 were also important serum molecules necessary to maintain optimum rosetting rates. The deactivation of complement network and serum depletion with C3 and C4 significantly reduced the rosette formation rate. The dependency of IgG and complement components also implied involvement of the complement receptor (CR1). Rosette formation test with Knops null RBC and sCR1 confirmed that CR1 is also part of Borrelia induced rosette formation.

Keywords: complement components C3 and C4, complement receptor 1, Immunoglobulin G, Knops null, Rosetting

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Authors: Rabia Ashfaq, Saeed Iqbal, Atiq ur Rehman, Irfanullah Khan

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An extensive series of radiopharmaceuticals have been explored in order to discover a better brain tumour diagnostic agent. Tc99m labelling with cysteine and its derivatives in liposomes shows effective tagging of about 70% to 80 %. Due to microscopic size it successfully crossed the brain barrier in 2 minutes which gradually decreases in 5 to 15 minutes. HMPAO labelled with Tc99m is another important radiopharmaceutical used to study brain perfusion but it comes with a flaw that it’s only functional during epilepsy. 1, 1 ECD is purely used in Tc99m ECD formulation; because it not only tends to cross the blood brain barrier but it can be metabolized which can be easily entrapped in human brain. Radio labelling of Cysteine with Tc99m at room temperature was performed which yielded no good results. Hence cysteine derivatives with salicylaldehyde were prepared that produced about 75 % yield for ligand. In order to perform it’s radio labelling a suitable solvent DMSO was selected and physical parameters were performed. Elemental analyser produced remarkably similar results for ligand as reported in literature. IR spectra of Ligand in DMSO concluded in the absence of SH stretch and presence of N-H vibration. Thermal analysis of the ligand further suggested its decomposition pattern with no distinct curve for a melting point. Radio labelling of ligand was performed which produced excellent results giving up to 88% labelling at pH 5.0. Clinical trials using Rabbit were performed after validating the products reproducibility. The radiopharmaceutical prepared was injected into the rabbit. Dynamic as well as static study was performed under the SPECT. It showed considerable uptake in the kidneys and liver considering it suitable for the Hypatobilliary study.

Keywords: marcapto compounds, 99mTc - radiolabeling, salicylaldicysteine, thiozolidine

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

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Authors: Doaa Hashad, Amany Elyamany, Perihan Salem

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Introduction: Hepatitis C virus infection (HCV) constitutes a serious dilemma that has an impact on the health of millions of Egyptians. Hepatitis C virus related hepatocellular carcinoma (HCV-HCC) is a crucial consequence of HCV that represents the third cause of cancer-related deaths worldwide. Aim of the study: assess the use of mitochondrial DNA (mtDNA) content as a non-invasive molecular biomarker in hepatitis c virus related hepatocellular carcinoma (HCV-HCC). Methods: A total of 135 participants were enrolled in the study. Volunteers were assigned to one of three groups equally; a group of HCV related cirrhosis (HCV-cirrhosis), a group of HCV-HCC and a control group of age- and sex- matched healthy volunteers with no evidence of liver disease. mtDNA was determined using a quantitative real-time PCR technique. Results: mtDNA content was lowest in HCV-HCC cases. No statistically significant difference was observed between the group of HCV-cirrhosis and the control group as regards mtDNA level. HCC patients with multi-centric hepatic lesions had significantly lower mtDNA content. On using receiver operating characteristic curve analysis, a cutoff of 34 was assigned for mtDNA content to distinguish between HCV-HCC and HCV-cirrhosis patients who are not yet complicated by malignancy. Lower mtDNA was associated with greater HCC risk on using healthy controls, HCV-cirrhosis, or combining both groups as a reference group. Conclusions: mtDNA content might constitute a non-invasive molecular biomarker that reflects tumor burden in HCV-HCC cases and could be used as a predictor of HCC risk in patients of HCV-cirrhosis. In addition, the non significant difference of mtDNA level between HCV-cirrhosis patients and healthy controls could eliminate the grey zone created by the use of AFP in some cirrhotic patients.

Keywords: DNA copy number, HCC, HCV, mitochondrial

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Authors: Niloofar Bahramian, Mohammad Atai, Mohammad Reza Naimi-Jamal

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Rule of mixtures is the simple analytical model is used to predict various properties of composites before design. The aim of this study was to demonstrate the benefits and limitations of the Rule-of-Mixtures (ROM) for predicting bending modulus of a continuous and unidirectional fiber reinforced composites using in dental applications. The Composites were fabricated from light curing resin (with and without silica nanoparticles) and modified and non-modified fibers. Composite samples were divided into eight groups with ten specimens for each group. The bending modulus (flexural modulus) of samples was determined from the slope of the initial linear region of stress-strain curve on 2mm×2mm×25mm specimens with different designs: fibers corona treatment time (0s, 5s, 7s), fibers silane treatment (0%wt, 2%wt), fibers volume fraction (41%, 33%, 25%) and nanoparticles incorporation in resin (0%wt, 10%wt, 15%wt). To study the fiber and matrix interface after fracture, single edge notch beam (SENB) method and scanning electron microscope (SEM) were used. SEM also was used to show the nanoparticles dispersion in resin. Experimental results of bending modulus for composites made of both physical (corona) and chemical (silane) treated fibers were in reasonable agreement with linear ROM estimates, but untreated fibers or non-optimized treated fibers and poor nanoparticles dispersion did not correlate as well with ROM results. This study shows that the ROM is useful to predict the mechanical behavior of unidirectional dental composites but fiber-resin interface and quality of nanoparticles dispersion play important role in ROM accurate predictions.

Keywords: bending modulus, fiber reinforced composite, fiber treatment, rule-of-mixtures

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Authors: Rong Yuan, Zhao Tao

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Only a handful of literature have used to non-linear model to investigate the influencing factors of greenhouse gas (GHG) emissions in China’s manufacturing sectors. And there is a limit in investigating quantitatively and systematically the mechanism of correlation between economic development and GHG emissions considering inherent differences among manufacturing sub-sectors. Considering the sectorial characteristics, the manufacturing sub-sectors with various impacts of output on GHG emissions may be explained by different development modes in each manufacturing sub-sector, such as investment scale, technology level and the level of international competition. In order to assess the environmental impact associated with any specific level of economic development and explore the factors that affect GHG emissions in China’s manufacturing industry during the process of economic growth, using the threshold Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, this paper investigated the influence impacts of GHG emissions for China’s manufacturing sectors of different stages of economic development. A data set from 28 manufacturing sectors covering an 18-year period was used. Results demonstrate that output per capita and investment scale contribute to increasing GHG emissions while energy efficiency, R&D intensity and FDI mitigate GHG emissions. Results also verify the nonlinear effect of output per capita on emissions as: (1) the Environmental Kuznets Curve (EKC) hypothesis is supported when threshold point RMB 31.19 million is surpassed; (2) the driving strength of output per capita on GHG emissions becomes stronger as increasing investment scale; (3) the threshold exists for energy efficiency with the positive coefficient first and negative coefficient later; (4) the coefficient of output per capita on GHG emissions decreases as R&D intensity increases. (5) FDI shows a reduction in elasticity when the threshold is compassed.

Keywords: China, GHG emissions, manufacturing industry, threshold STIRPAT model

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Authors: Tetyana Kendzerska, David T. Zhu, Michael Pugliese, Douglas Manuel, Mohsen Sadatsafavi, Marcus Povitz, Therese A. Stukel, Teresa To, Shawn D. Aaron, Sunita Mulpuru, Melanie Chin, Claire E. Kendall, Kednapa Thavorn, Rebecca Robillard, Andrea S. Gershon

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The impact of the COVID-19 pandemic on the management of ambulatory care sensitive conditions (ACSCs) remains unknown. To compare observed and expected (projected based on previous years) trends in all-cause mortality and healthcare use for ACSCs in the first year of the pandemic (March 2020 - March 2021). A population-based study using provincial health administrative data.General adult population (Ontario, Canada). Monthly all-cause mortality, and hospitalizations, emergency department (ED) and outpatient visit rates (per 100,000 people at-risk) for seven combined ACSCs (asthma, COPD, angina, congestive heart failure, hypertension, diabetes, and epilepsy) during the first year were compared with similar periods in previous years (2016-2019) by fitting monthly time series auto-regressive integrated moving-average models. Compared to previous years, all-cause mortality rates increased at the beginning of the pandemic (observed rate in March-May 2020 of 79.98 vs. projected of 71.24 [66.35-76.50]) and then returned to expected in June 2020—except among immigrants and people with mental health conditions where they remained elevated. Hospitalization and ED visit rates for ACSCs remained lower than projected throughout the first year: observed hospitalization rate of 37.29 vs. projected of 52.07 (47.84-56.68); observed ED visit rate of 92.55 vs. projected of 134.72 (124.89-145.33). ACSC outpatient visit rates decreased initially (observed rate of 4,299.57 vs. projected of 5,060.23 [4,712.64-5,433.46]) and then returned to expected in June 2020. Reductions in outpatient visits for ACSCs at the beginning of the pandemic combined with reduced hospital admissions may have been associated with temporally increased mortality—disproportionately experienced by immigrants and those with mental health conditions. The Ottawa Hospital Academic Medical Organization

Keywords: COVID-19, chronic disease, all-cause mortality, hospitalizations, emergency department visits, outpatient visits, modelling, population-based study, asthma, COPD, angina, heart failure, hypertension, diabetes, epilepsy

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Authors: Vadim A. Kuznetsov, Anna M. Soldatova, Tatyana N. Enina, Elena A. Gorbatenko, Dmitrii V. Krinochkin

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The aim of the study was to evaluate potential parameters related with super-response to CRT. Methods: 60 CRT patients (mean age 54.3 ± 9.8 years; 80% men) with congestive heart failure (CHF) II-IV NYHA functional class, left ventricular ejection fraction < 35% were enrolled. At baseline, 1 month, 3 months and each 6 months after implantation clinical, electrocardiographic and echocardiographic parameters, NT-proBNP level were evaluated. According to the best decrease of left ventricular end-systolic volume (LVESV) (mean follow-up period 33.7 ± 15.1 months) patients were classified as super-responders (SR) (n=28; reduction in LVESV ≥ 30%) and non-SR (n=32; reduction in LVESV < 30%). Results: At baseline groups differed in age (58.1 ± 5.8 years in SR vs 50.8 ± 11.4 years in non-SR; p=0.003), gender (female gender 32.1% vs 9.4% respectively; p=0.028), width of QRS complex (157.6 ± 40.6 ms in SR vs 137.6 ± 33.9 ms in non-SR; p=0.044). Percentage of LBBB was equal between groups (75% in SR vs 59.4% in non-SR; p=0.274). All parameters of mechanical dyssynchrony were higher in SR, but only difference in left ventricular pre-ejection period (LVPEP) was statistically significant (153.0 ± 35.9 ms vs. 129.3 ± 28.7 ms p=0.032). NT-proBNP level was lower in SR (1581 ± 1369 pg/ml vs 3024 ± 2431 pg/ml; p=0.006). The survival rates were 100% in SR and 90.6% in non-SR (log-rank test P=0.002). Multiple logistic regression analysis showed that LVPEP (HR 1.024; 95% CI 1.004–1.044; P = 0.017), baseline NT-proBNP level (HR 0.628; 95% CI 0.414–0.953; P=0.029) and age at baseline (HR 1.094; 95% CI 1.009-1.168; P=0.30) were independent predictors for CRT super-response. ROC curve analysis demonstrated sensitivity 71.9% and specificity 82.1% (AUC=0.827; p < 0.001) of this model in prediction of super-response to CRT. Conclusion: Super-response to CRT is associated with better survival in long-term period. Presence of LBBB was not associated with super-response. LVPEP, NT-proBNP level, and age at baseline can be used as independent predictors of CRT super-response.

Keywords: cardiac resynchronisation therapy, superresponse, congestive heart failure, left bundle branch block

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Authors: Roghaieh Parvizsedghy, Seyed Mojtaba Sadrameli

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Diminishing oil reserves, deteriorating health standards because of greenhouse gas emissions and associated environmental impacts have emerged biofuel production. Vegetable oils are proved to be valuable feedstock in these growing industries as they are renewable and potentially inexhaustible sources. Thermal Cracking of vegetable oils (triglycerides) leads to production of biofuels which are similar to fossil fuels in terms of composition but their combustion and physical properties have limits. Acrolein (very poisonous gas) and water production during cracking of triglycerides occurs because of presence of glycerin in their molecular structure. Transesterification of vegetable oil is a method to extract glycerol from triglycerides structure and produce methyl ester. In this study, castor methyl ester was used for thermal cracking in order to survey the efficiency of this method to produce bio-gasoline and bio-diesel. Thus, several experiments were designed by means of central composite method. Statistical studies showed that two reaction parameters, namely cracking temperature and feed flowrate, affect products yield significantly. At the optimized conditions (480 °C and 29 g/h) for maximum bio-gasoline production, 88.6% bio-oil was achieved which was distilled and separated as bio-gasoline (28%) and bio-diesel (48.2%). Bio-gasoline exposed a high octane number and combustion heat. Distillation curve and Reid vapor pressure of bio-gasoline fell in the criteria of standard gasoline (class AA) by ASTM D4814. Bio-diesel was compatible with standard diesel by ASTM D975. Water production was negligible and no evidence of acrolein production was distinguished. Therefore, thermal cracking of castor methyl ester could be used as a method to produce valuable biofuels.

Keywords: bio-diesel, bio-gasoline, castor methyl ester, thermal cracking, transesterification

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Authors: Fatima Zahra Mahjoubi, Abderrahim Khalidi, Mohammed Abdennouri, Noureddine Barka

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Zn-Al layered double hydroxides containing carbonate, nitrate and dodecylsulfate as the interlamellar anions have been prepared through a coprecipitation method. The resulting compounds were characterized using XRD, ICP, FTIR, TGA/DTA, TEM/EDX and pHPZC analysis. The XRD patterns revealed that carbonate and nitrate could be intercalated into the interlayer structure with basal spacing of 22.74 and 26.56 Å respectively. Bilayer intercalation of dodecylsulfate molecules was achieved in Zn-Al LDH with a basal spacing of 37.86 Å. The TEM observation indicated that the materials synthesized via coprecipitation present nanoscale LDH particle. The average particle size of Zn-AlCO3 is 150 to 200 nm. Irregular circular to hexagonal shaped particles with 30 to 40 nm in diameter was observed in the Zn-AlNO3 morphology. TEM image of Zn-AlDs display nanostructured sheet like particles with size distribution between 5 to 10 nm. The sorption characteristics and mechanisms of methyl orange dye on organic LDH were investigated and were subsequently compared with that on the inorganic Zn-Al layered double hydroxides. Adsorption experiments for MO were carried out as function of solution pH, contact time and initial dye concentration. The adsorption behavior onto inorganic LDHs was obviously influenced by initial pH. However, the adsorption capacity of organic LDH was influenced indistinctively by initial pH and the removal percentage of MO was practically constant at various value of pH. As the MO concentration increased, the curve of adsorption capacity became L-type onto LDHs. The adsorption behavior for Zn-AlDs was proposed by the dissolution of dye in a hydrophobic interlayer region (i.e., adsolubilization). The results suggested that Zn-AlDs could be applied as a potential adsorbent for MO removal in a wide range of pH.

Keywords: adsorption, dodecylsulfate, kinetics, layered double hydroxides, methyl orange removal

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Authors: Amritanshu Sandilya, M. V. Shah

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Collapsible soils such as loess are a common geotechnical challenge due to their potential to undergo sudden and severe settlement under certain loading conditions. The need for filling engineering to increase developing land has grown significantly in recent years, which has created several difficulties in managing soil strength and stability during compaction. Numerous engineering problems, such as roadbed subsidence and pavement cracking, have been brought about by insufficient fill strength. Therefore, strict control of compaction parameters is essential to reduce these distresses. Accurately measuring the degree of compaction, which is often represented by compactness is an important component of compaction control. For credible predictions of how collapsible soils will behave under complicated loading situations, the accuracy of laboratory studies is essential. Therefore, this study aims to investigate the energy transfer in collapsible soils during laboratory Proctor compaction tests to provide insights into how energy transfer can be optimized to achieve more accurate and reliable results in compaction testing. The compaction characteristics in terms of energy of loess soil have been studied at moisture content corresponding to dry of optimum, at the optimum and wet side of optimum and at different compaction energy levels. The hammer impact force (E0) and soil bottom force (E) were measured using an impact load cell mounted at the bottom of the compaction mould. The variation in energy consumption ratio (E/ E0) was observed and compared with the compaction curve of the soil. The results indicate that the plot of energy consumption ratio versus moisture content can serve as a reliable indicator of the compaction characteristics of the soil in terms of energy.

Keywords: soil compaction, proctor compaction test, collapsible soil, energy transfer

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

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Authors: Mapula Mothomogolo, Anria Clarke

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Ballistic grilles are adopted on military vehicles to mitigate the vulnerability of the radiator. The design of ballistic grilles needs to address conflicting requirements: shielding the surface area of the radiator from incoming projectile threats yet providing sufficient airflow through the radiator to yield adequate heat rejection. These conflicting requirements result in a unique and challenging design problem. In this paper, the airflow through a ballistic grille using a computational modelling approach is investigated. A comparative study was conducted between a standard grille and a ballistic grille of a military vehicle. The results were used as a benchmark study for optimizing the ballistic grille with pressure drop selected as the parameter for optimization. The grilles were modelled as a porous medium to account for the pressure drop in the porous region. The effects of the porous zone were accounted for in the source term of the momentum Navier Stokes equations. The source term defines the pressure drop in the porous region as a function of the velocity. A pressure drop curve approach was used to determine the Darcy coefficient and inertial resistance coefficients of the source terms. The empirically defined coefficients were used as simulation input for a more accurate pressure drop prediction in the porous region. Additionally, the ballistic grille was optimized using an adjoint solver (shape optimization module in Ansys Fluent) to reduce the pressure drop through the ballistic grille by 30%. Based on the simulation results, the optimized ballistic grille geometry needs to be experimentally tested to validate the numerical simulation data.

Keywords: ballistic grille, darcy coefficient, optimization, porous medium

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