Desired Level Research Articles

An efficient modelling technique for simulation of guided waves in delaminated composite and sandwich structures

The paper presents a higher order laminate model with sub-lamination capability for simulating wave propagation within delaminated composite and sandwich beams. Each sub-laminate adopts cubic and quadratic through-thickness variation for axial and transverse displacement, respectively. This is achieved by taking displacements at external surfaces, which are beneficial for connecting sub-laminates, used to model multilayered structures by stacking them in the thickness direction without additional treatment. The model has the flexibility to achieve the desired level of accuracy and computational efficiency by using a suitable sub-lamination scheme. The delamination can be inserted conveniently between two sub-laminates stacked one over the other. The effect of contact within delamination regions is also incorporated in this model to capture higher harmonics induced by a clapping mechanism produced during delamination closing. The model is implemented within a framework of spectral finite elements in the time-domain. The accuracy and computational efficiency of the model are thoroughly checked by solving numerical examples of wave propagation within intact/delaminated composite/sandwich beams. Detailed finite element (FE) models used to produce results for validation show that the proposed model can save more than 90% of computing time and memory compared to detailed FE modelling to achieve similar level accuracy. The model is finally utilised to investigate the influence of delamination sizes and location on the wave response of sandwich beams.

The development of a generalized multilevel inverter for symmetrical and asymmetrical dc sources with a minimized ON state switch

This paper proposes a double source double diode double switch (DSDDDS) multilevel inverter to generate positive voltage and a connecting polarity changing circuit of an H-bridge inverter to generate negative voltage. By connecting the jth number of basic units in series, the desired level is obtained. Various algorithms, such as Natural, Binary, Trinary, and Quasi-Linear sequences, and two proposed algorithms are discussed to determine the magnitude of DC voltage sources in order to generate more stepped levels with fewer switches. The proposed multilevel inverter eliminates the need to turn on additional power switches for different levels, which is the main advantages of this topology. The proposed multilevel inverter is compared to conventional switched diode multilevel inverters in terms of switch count, number of ON state switches per level, driver circuits, and total standing voltage. Real-time results from the OPAL-RT test bench and simulation have validated the proposed inverter.

Chemical, physical properties, microstructure and granulometric composition of ultra-finely ground chicken bone paste

The article describes a method for processing chicken bones from the neck, leg, breast, and wing in order to obtain finely dispersed chicken meat-bone paste (MBP). Bones were crushed two times: (a) with a bone chopper (particle size ≤ 5 mm), (b) ultrafine grinding machine (particle size ≤ 0.1 mm). Thereafter, ice water was added in different ratios (0%, 25%, 50%, 75%, 100%) into crushed bones. The effect of added water on the temperature, water binding capacity and chemical composition of MBP was studied. An increase in the proportion of water in MBP during ultrafine grinding leads to a decrease in the water binding capacity. The addition of water to crushed chicken bones followed by ultrafine grinding causes an increase in moisture content and a decrease in fat, protein and ash contents of meat-bone paste. After ultrafine grinding the size of >80% of bone particles is < 0.1 mm, and the remaining portion is < 0.25 mm. The optimal way of processing MBP is a two-stage grinding with preliminary freezing, crushing on the bone chopper, adding 50% of water to the mass of chopped bone, and finally ultrafine grinding. This processing method makes it possible to obtain MBP with good water binding capacity, homogeneous consistency, and balanced chemical composition. Practical implicationsWaste-free processing of poultry bones can help processing plants reduce labor and energy costs, make more efficient use of production capacity, and improve the profitability of poultry production as a whole. This information can guide manufacturers in achieving desired moisture levels and consistency in the final product. It also highlights the importance of controlling the water-to-MBP ratio during the grinding process to meet specific quality and moisture requirements.

Technology-enabled leadership and performance enhancement outcomes: an empirical investigation from the dynamic capabilities perspective

PurposeThis paper aims to examine the role of technology-enabled leadership (TEL) in achieving performance-enhancement outcomes. This empirical investigation is from a dynamic capabilities perspective.Design/methodology/approachA conceptual framework presents a general model with an overarching dynamic capabilities theory. The research model defines key variables – macroeconomic turbulence (MET), TEL, analytics-based responsiveness (ABR), knowledge-driven innovation (KDI) and performance enhancement outcomes (PEOs). Empirical tests of eight hypotheses are conducted using an original survey instrument based on the respondents (n = 203).FindingsIn response to MET, TEL is crucial in implementing ABR in strategic planning aspects and KDI in operational dimensions. In turn, ABR and KDI are key mediating variables that achieve a desirable level of PEOs.Research limitations/implicationsDespite the limitations associated with survey-based research, the findings suggest robust analytical results. For example, the alternative model suggests that MET negatively moderates the positive impact of TEL on ABR, while KDI positively moderates the positive impact of ABR on PEOs.Practical implicationsOutstanding firms demonstrate both TEL and data-savvy decision-making processes. Knowledge-intensive innovation allows firms to achieve multiple performance outcomes that help firms survive and thrive in challenging market environments.Social implicationsThere has been a growing concern about how firms use customers’ data in choosing their business practices. Customers are concerned about privacy and data security issues if firms misuse the data while pursuing profit-based goals. However, this empirical investigation confirms that business analytics improve firm performance (e.g. firm productivity enhancements), ultimately benefiting the customers. Providing relevant data to firms has potentially positively enhanced customer services and thus benefits societal well-being.Originality/valueUsing an original survey instrument, this research empirically tests a research model that defines the complex paths between TEL and competitive performance outcomes.

An automated optical inspection (AOI) platform for three-dimensional (3D) defects detection on glass micro-optical components (GMOC)

With the widespread deployment of wavelength division multiplexing (WDM), optical transceivers increasingly use many glass micro-optical components (GMOC). Visual inspection of these GMOCs is a critical manufacturing step to ensure quality and reliability. However, manual inspection is often labor-intensive and time-consuming due to the transparent nature of glass components and the small, randomly located defects in three dimensions. Although automated optical inspection (AOI) exists, it has not yet been able to provide the desired level of accuracy and efficiency.This paper reports the development of an AOI platform for 3D defect detection on GMOCs. The platform incorporates 3D video acquisition and a novel two-stage neural network machine-learning algorithm. It includes a robotic arm for moving parts in 3D, a camera with an illumination module for video acquisition, and a video streaming processing unit with a machine vision algorithm for real-time defect detection on a production line. The robotic arm enables multi-perspective video capture of a test sample without refocusing. The two-stage machine learning network uses a modified YOLOv4 architecture with color channel separation (CCS) convolution, an image quality evaluation (IQE) module, and a frame fusion module to integrate the single frame detection results. This network can process multi-perspective video streams in real-time for defects detection in a coarse-to-fine manner. The AOI platform was trained with only 30 samples and achieved promising performances with a recall rate of 1, a detection accuracy of 97%, and an inspection time of 48 s per part.

Development and evaluation of a customized checklist to assess the quality control of disease registry systems of Tehran, the capital of Iran in 2021

BackgroundClinical registries facilitate medical research by providing ‘real data’. In the past decade, an increasing number of disease registry systems (DRS) have been initiated in Iran. Here, we assessed the quality control (QC) of the data recorded in the DRS established by Shahid Beheshti University of Medical Sciences in Tehran, the capital city of Iran, in 2021.MethodsThe present study was conducted in two consecutive qualitative and quantitative phases and employed a mixed-method design. A checklist containing 23 questions was developed based on a consensus reached following several panel group discussions, whose face content and construct validities were confirmed. Cronbach’s alpha was calculated to verify the tool’s internal consistency. Overall, the QC of 49 DRS was assessed in six dimensions, including completeness, timeliness, accessibility, validity, comparability, and interpretability. The seventy percent of the mean score was considered a cut-point for desirable domains.ResultsThe total content validity index (CVI) was obtained as 0.79, which is a reasonable level. Cronbach’s alpha coefficients obtained showed acceptable internal consistency for all of the six QC domains. The data recorded in the registries included different aspects of diagnosis/treatment (81.6%) and treatment quality requirements outcomes (12.2%). According to the acceptable quality cut-point, out of 49 evaluated registries, 48(98%), 46(94%), 41(84%), and 38(77.5%), fulfilled desirable quality scores in terms of interpretability, accessibility, completeness, and comparability, however, 36(73.5%) and 32(65.3%) of registries obtained the quality requirement for timeliness and validity, respectively.ConclusionThe checklist developed here, containing customized questions to assess six QC domains of DRSs, provided a valid and reliable tool that could be considered as a proof-of-concept for future investigations. The clinical data available in the studied DRSs fulfilled desirable levels in terms of interpretability, accessibility, comparability, and completeness; however, timeliness and validity of these registries needed to be improved.

Balancing economic benefits and environmental repercussions based on smart irrigation by regulating root zone water and salinity dynamics

As a critical index for irrigation scheduling, plant water deficit index (PWDI) is defined as the ratio of water deficit to water demand to reflect the extent of abiotic stresses such as water and salinity. Recently, smart irrigation scheduling, according to PWDI thresholds to maintain desirable or acceptable stress levels, has been suggested to maximize yields while minimizing negative environmental effects under non-saline conditions. To investigate and quantify the potential for PWDI-driven irrigation on agricultural production under conditions of salinity, a two-year experiment with six specific thresholds was conducted in Shawan of Xinjiang for drip-irrigated cotton under film mulch. Results indicated that, with increasing PWDI threshold, irrigation depth per event increased, while irrigation frequency and total volume decreased. Consequently, the soil water and salt environment deteriorated, resulting in less nutrient uptake, slower growth, and lower yield and net profit. With particularly high PWDI thresholds leading to serious stress conditions, fiber quality was also negatively affected. Within a designed range of PWDI thresholds between 0.39 and 0.62, an elliptic function characterized the processes of water application, yield and net profit (R2 ≥ 0.95), and water productivity could be described by a parabolic function (R2 = 0.77). These quantitative results were used to provide guidelines for smart irrigation scheduling under local conditions considering water management measures and market prices of cotton. For a reference market price of 7.5 CNY kg-1, a PWDI threshold of 0.49 was found to optimize economic benefits while maximizing water productivity. When prices of cotton are prohibitively low, a lower threshold should be considered to obtain an acceptable net profit. Otherwise, a higher threshold would be preferable to use water more efficiently. Further verification and improvement are necessary to deal with more complex scenarios, such as, considering crop sensitivity to water and salinity stresses at different growth stages and optimizing irrigation depth per event.

Switched-Capacitor-Based Multi-Source Multilevel Inverter With Reduced Part Count

This paper proposes a switched-capacitor (SC) based multi-source multilevel inverter (MSMLI) for high-frequency AC power distribution systems. The proposed topology is a potential alternative in applications involving asymmetric dc voltage sources (in the case of renewable source-based AC microgrids). Using the available dc sources as an aggregated input eliminates the need for paralleling of inverters. In addition, the proposed topology offers a common ground among the multiple input sources and, thus, has a more straight forward design and avoids stacking voltage sources. By employing nine switches, two diodes, and two SCs, an 11-level voltage waveform is synthesized. The SC voltages are self-balanced owing to their series-parallel charging technique. A simple selective harmonic elimination technique is used to obtain the desired output voltage level and simultaneously eliminate the lower-order harmonics. A detailed comparison of the proposed MSMLI is carried out, and the test results obtained from a laboratory prototype are presented to validate the feasibility and highlight the benefits of the proposed topology.

Modeling and Validation of a Lithium-Ion Battery Pack

Abstract Batteries are part of an extremely nonlinear electrochemical system, and their performance is determined by various key factors such as law of thermodynamics, electrode kinetics, ion transport, and diffusion. To develop an accurate model of a battery, it is important to take into consideration both the internal and external conditions that would determine both the battery dynamics and its performance. Electrochemical, mathematical, and electrical equivalent circuit models are three common ways to model the electrochemical battery system. However, using these models involves certain limitations such as increased computation, empirical equations, and components (both active and passive). A simple electrical battery model with a voltage source and a resistor is insufficient to attain the desired level of accuracy in the model. To overcome these limitations, this study presents an electrothermal model that has been designed by adding “n” number of resistance capacitance (RC) pairs connected parallelly to ensure both dynamics and accuracy. An electrothermal model of a lithium-ion cell with a one-RC model and two-RC model has been developed, and a performance comparison has also been made to check the voltage accuracy of all the models. The electrical and thermal parameters (Em (state of charge [SOC], T), RO (SOC, T), R1 (SOC, T), R2 (SOC, T), C1 (SOC, T), C2 (SOC, T)) required for an RC model have been extracted through the pulse charge-discharge test. A battery pack of 55 V, 50 Ah using the RC model based on the Indian driving cycle condition has also been developed. Pulse charge-discharge and constant current-constant voltage profiles have been applied to the developed battery pack model to simulate and validate the accuracy of voltage in a real-time scenario.

Determination of the Effect of Different Doses of ECG Applications on Reproductive Parameters in Primiparous Akkaraman Kangal Sheep

To increase meat production at a level parallel to meet the demand of the increasing world population in recent years, reproductive management in farm animals must be successful. In order to reach the desired level of fertility in sheep, particularly starting with the non-prolific breeds, anoestrus period applications should be carried out effectively. In this study, different doses of equine chorionic gonadotropin were applied to determine the effective eCG dose for underwent estrus synchronization with progesterone in anoestrus Kangal ewes whose milk and wool yield has been completely abandoned by the breeder for various reasons and whose only economic benefit is lamb production. A total of 225 Kangal Akkaraman Sheep breeds, 2 years old, with a body condition score of 2.5-3.5 and an average weight of 40-50 kg, were included in the study. In line with this purpose, ewes were divided into 3 groups, containing 75 primiparous sheep. A vaginal sponge containing progesterone was inserted into the animals in all groups on day 0. Seven days after this application (on the 7th day), vaginal sponges were removed and Prostaglandin F2α (PGF2α) was applied. When the vaginal sponge was removed and the PGF2α was administered, 400 IU of eCG was given to animals in Group 1 (n:75), 500 IU of eCG was administrated to animals in Group 2 (n:75), and 600 IU of eCG was injected to the ewes in Group 3. The effectiveness of different doses of eCG application on reproductive parameters such as estrous rate, pregnancy rate, multiple pregnancy rate, and the number of offspring was evaluated. While no statistical difference could be determined between the groups in terms of the stated reproductive parameters, numerically more offspring were obtained in the group in which eCG was applied at a low rate (Group 1). In the light of this information, it is concluded that 400 IU eCG can be as effective as 600 IU eCG in sexual stimulation of Kangal ewes in anestrus.

Frequency and Awareness of Diabetes Mellitus in Participants of Primary Healthcare in the Capital of Turkey

Introduction: Awareness-based approaches are proven to reduce disease-related complications, depressive symptoms, anxiety during the disease process, economic losses due to disease, and improve quality of life in diabetes patients. This study aims to present the frequency and awareness of diabetes mellitus in patients who applied to a primary health care institution in the capital city of Turkey. Materials and Methods: This cross-sectional study was conducted in the capital city of Turkey. In statistical analysis; descriptive statistics, Mann Whitney U, Kruskal Wallis and logistic regression analysis methods were employed for the statistical analysis part of this research. Results: 24.4% of the participants had diabetes. Regarding diabetes awareness level, statistically significant differences were found in age, education level, marital status, income, attention to healthy nutrition, BMI and presence of chronic disease. Employment variable has been identified as the factor that affected the diabetes awareness score the most in multiple logistic regression analysis. When only the participants with diabetes were examined in the multiple logistic regression analysis, it was found that the factor affecting the diabetes awareness score the most was diabetes type. Other influencing factors were determined as diet for diabetes and receiving diabetes education, respectively. Conclusion: Despite of many research that were carried out under the roof of diabetes awareness in the world and in Turkey, the desired level of knowledge and awareness is yet to be reached. Further research needs to be conducted in order to reach this goal

A new approach for designing the Shewhart-type control charts with generalized sensitizing rules

Two commonly used approaches for developing a Shewhart-type control chart with sensitizing rules are; the Markov Chain approach (MCA) and the single polynomial approach (SPA). The MCA for designing a control chart involves linear equations based on the choice of sensitizing rules. The MCA often becomes complex as the system of linear equations increases in size. The existing SPA for designing a control chart with sensitizing rules results in inconsistent in-control run length properties (RLP). To overcome the limitations of existing approaches, we present a new SPA for designing the Shewhart-type control charts with sensitizing rules. Furthermore, the new SPA has an interesting relationship with classical geometric distribution, generalized geometric distribution, and MCA. To show the significance of the new SPA, we have implemented it in designing the two-sided and one-sided mean control charts with sensitizing rules. The performance of the proposed and existing control charts is evaluated and compared using various RLP. The results reveal that the in-control RLP of the new SPA based mean control charts are sustained at their desired level. The out-of-control RLP is elaborated to highlight an optimal choice of sensitizing rules and other factors. Extensive comparative analysis shows that the new SPA based mean control charts have advantages over sustained behavior and computational reduction. Lastly, a real-life example of proposed methods is included using data on turnaround time of complete blood count (CBC) test results.

Оценка привлекательности жизни в российской Арктике (на примере Мурманской области)

In recent decades, the population in the Arctic territories of the Russian Federation has been declining, which indicates the need for sociological monitoring of the development problems of this territory, which will make it possible to update measures to increase its attractiveness to the population. The purpose of this study is to identify the level of attractiveness of the Arctic territories based on the example of the Murmansk region in the views of its residents. According to a questionnaire survey (N = 444) and an indepth interview (N = 30) conduct-ed by the authors in 2020, it was found that unfavorable environmental and climatic conditions, the views of the population on the lack of prospects for self-realization in the professional and social spheres of life, and oppor-tunities for achieving the desired level of material and social well-being contribute to reducing the positive per-ception of the region. The study leads to the conclusion that it is necessary to take measures to increase the attractiveness of the Arctic territories as a place of residence. The obtained results can be useful in the regional programs for the development and improvement of the quality of life of the population of the Arctic zone of the Russian Federation.

Bank risk exposures and bank stability in Africa: the role of regulations in a non-linear model

PurposeThis paper aims to examine the interaction effect of regulations (monetary and macro-prudential) in explaining the possible non-linear effect of bank risk exposures (credit risk and insolvency risk) on banking stability in Africa.Design/methodology/approachThe study uses a two-step system generalized method of moments (GMM) estimator for a data set of banks across 54 African countries over the period 2006–2020.FindingsThe authors find that the relationships between bank credit risk–bank stability and bank insolvency risk–bank stability are non-linear and characterized by the presence of optimal thresholds, which are 5.3456 for credit risk and 2.3643 for insolvency. Contrary to their positive effects below these optimal thresholds, credit risk and insolvency risk become negatively linked to bank stability in Africa. The authors find that macro-prudential action and monetary policy both have a positive and significant relationship with bank stability. The authors provide evidence to support that the marginal effect of excessive credit risk and insolvency risk on bank stability is reduced when interacted with monetary and macro-prudential regulations, and the impact is significant in strong institutional environment.Research limitations/implicationsFuture research should extend data to include developing and emerging economies in the world. Also, policymakers, researchers and practitioners should consider different regulatory and institutional frameworks in explaining the relationship between the thresholds of bank risk exposures and bank stability in the world.Practical implicationsRegulatory authorities should have to deeply reform their financial systems, develop risk-based regulatory framework and effective supervision mechanism relating to appropriate techniques that maintain an optimal and desired level of bank risks and risk-taking behaviours required to ensure a stable banking system.Originality/valueTo the best of the authors’ knowledge, this is the first study to examine how different regulatory frameworks shape the non-linear impact of bank risk exposures on bank stability in Africa.

Model reference adaptive system speed estimator based on type-1 and type-2 fuzzy logic sensorless control of electrical vehicle with electrical differential

Introduction. In this paper, a new approach for estimating the speed of in-wheel electric vehicles with two independent rear drives is presented. Currently, the variable-speed induction motor replaces the DC motor drive in a wide range of applications, including electric vehicles where quick dynamic response is required. This is now possible as a result of significant improvements in the dynamic performance of electrical drives brought about by technological advancements and development in the fields of power commutation devices, digital signal processing, and, more recently, intelligent control systems. The system’s reliability and robustness are improved, and the cost, size, and upkeep requirements of the induction motor drive are reduced through control strategies without a speed sensor. Successful uses of the induction motor without a sensor have been made for medium- and high-speed operations. However, low speed instability and instability under various charge perturbation conditions continue to be serious issues in this field of study and have not yet been effectively resolved. Some application such as traction drives and cranes are required to maintain the desired level of torque down to low speed levels with uncertain load torque disturbance conditions. Speed and torque control is more important particularly in motor-in-wheel traction drive train configuration where vehicle wheel rim is directly connected to the motor shaft to control the speed and torque. Novelty of the proposed work is to improve the dynamic performance of conventional controller used of model reference adaptive system speed observer using both type-1 and type-2 fuzzy logic controllers. Purpose. In proposed scheme, the performance of the engine is being controlled, fuzzy logic controller is controlling the estimate rotor speed, and results are then compared using type-1 and type-2. Method. For a two-wheeled motorized electric vehicle, a high-performance sensorless wheel motor drive based on both type-2 and type-1 fuzzy logic controllers of the model reference adaptive control system is developed. Results. Proved that, using fuzzy logic type-2 controller the sensorless speed control of the electrical differential of electric vehicle EV observer, much better results are achieved. Practical value. The main possibility of realizing reliable and efficient electric propulsion systems based on intelligent observers (type-2 fuzzy logic) is demonstrated. The research methodology has been designed to facilitate the future experimental implementation on a digital signal processor.

The Impact of Economic Corridor and Tourism on Local Community's Quality of Life under One Belt One Road Context.

Economic corridors unlock new economic opportunities and tourism development in the region to achieve sustainable development goals. Green economic growth is conducive to environmental sustainability. Economic mega-projects of CPEC promote tourism that leads to communities' well-being and better quality of life. Modern infrastructure development contributes significantly to economic growth and tourism activities. This study's objectives emphasize exploring tourism and sustainable development pursuits under OBOR economic projects that open doors to improving residents' quality of life. The growing world is an eyewitness to a continuous rise in emissions and its severe consequences for humankind. It is necessary to show off the leading factors that result in tourism and economic activities causing environmental pollution rather than blame policymakers. Undoubtedly, many studies previously focused on demonstrating the influence of socio-economic factors that lead to better environmental quality. However, the empirical literature on tourism, social well-being, foreign direct investment, and the Environment in Belt and Road developed economies needed improvement. This research applied a series of advanced estimators that help demonstrate the study's probable results. This study explores the role of Social well-being (HDI), tourism development, FDI, renewable energy, information & communication technology (ICT), and urbanization on CO2 emissions in Belt and Road (BRI) developed economies.Estimated results exhibited the significant contribution of ICT and renewable energy to sustainability. Besides, FDI contributes to emissions reduction after its threshold level. Conversely, urbanization and tourism activities contribute to environmental pollution. The study outcomes stated inverted/EKC U-shaped hypotheses related to specified economies. Finally, the analysis based on the D-H panel causality test constructs exciting results.The present study concludes that economic corridor plays a vital role in tourism development, the community's well-being, and SDGs goals (sustainable development) impact on environmental safety. The findings suggest essential and applicable policies to attain the desired sustainability level. Findings contribute to the literature on tourism, well-being, and sustainability. Further studies can use insights using this methodology.

Hypergraph Artificial Benchmark for Community Detection (h–ABCD)

Abstract The Artificial Benchmark for Community Detection (ABCD) graph is a recently introduced random graph model with community structure and power-law distribution for both degrees and community sizes. The model generates graphs with similar properties as the well-known Lancichinetti, Fortunato, Radicchi (LFR) one, and its main parameter ξ can be tuned to mimic its counterpart in the LFR model, the mixing parameter μ. In this article, we introduce hypergraph counterpart of the ABCD model, h–ABCD, which also produces random hypergraph with distributions of ground-truth community sizes and degrees following power-law. As in the original ABCD, the new model h–ABCD can produce hypergraphs with various levels of noise. More importantly, the model is flexible and can mimic any desired level of homogeneity of hyperedges that fall into one community. As a result, it can be used as a suitable, synthetic playground for analyzing and tuning hypergraph community detection algorithms. [Received on 22 October 2022; editorial decision on 18 July 2023; accepted on 19 July 2023]

Model-Informed Support of Dose Selection for Prophylactic Treatment with Dalcinonacog Alfa in Adult and Paediatric HemophiliaB Patients.

Dalcinonacog alfa (DalcA), a novel subcutaneously administered recombinant human factorIX (FIX) variant is being developed for adult and paediatric patients with hemophiliaB (HB). DalcA has been shown to raise FIX to clinically meaningful levels in adults with HB. This work aimed to support dosing regimen selection in adults and perform first-in-paediatric dose extrapolations using a model-based pharmacokinetic (PK) approach. A population PK model was built using adult data from two clinical trials (NCT03186677, NCT03995784). With allometry in the model, clinical trial simulations were performed to study alternative dosing regimens in adults and children. Steady-state trough levels and the time-to-reach target were derived to inform dose selection. Almost 90% of the adults were predicted to achieve desirable FIX levels, i.e. 10% FIX activity, following daily 100IU/kg dosing, with 90% of the subjects reaching target within 1.6-7.1days. No every-other-day regimen met the target. A dose of 125IU/kg resulted in adequate FIX levels down to 6years, whereas a 150IU/kg dose was needed below 6 down to 2years of age. For subjects down to 6years that did not reach target with 125IU/kg, a dose escalation to 150IU/kg was appropriate. The children below 6 to 2years were shown to need a dose escalation to 200IU/kg if 150IU/kg given daily was insufficient. This study supported the adult dose selection for DalcA in the presence of sparse data and enabled first-in-paediatric dose selection to achieve FIX levels that reduce risk of spontaneous bleeds.

AutoScaleDSE: A Scalable Design Space Exploration Engine for High-Level Synthesis

High-Level Synthesis (HLS) has enabled users to rapidly develop designs targeted for FPGAs from the behavioral description of the design. However, to synthesize an optimal design capable of taking better advantage of the target FPGA, a considerable amount of effort is needed to transform the initial behavioral description into a form that can capture the desired level of parallelism. Thus, a design space exploration (DSE) engine capable of optimizing large complex designs is needed to achieve this goal. We present a new DSE engine capable of considering code transformation, compiler directives (pragmas), and the compatibility of these optimizations. To accomplish this, we initially express the structure of the input code as a graph to guide the exploration process. To appropriately transform the code, we take advantage of ScaleHLS based on the multi-level compiler infrastructure (MLIR). Finally, we identify problems that limit the scalability of existing DSEs, which we name the “design space merging problem.” We address this issue by employing a Random Forest classifier that can successfully decrease the number of invalid design points without invoking the HLS compiler as a validation tool. We evaluated our DSE engine against the ScaleHLS DSE, outperforming it by a maximum of 59×. We additionally demonstrate the scalability of our design by applying our DSE to large-scale HLS designs, achieving a maximum speedup of 12× for the benchmarks in the MachSuite and Rodinia set.

ABRAZIVE FLUID - MEANS OF IMPROVEMENT THE GEOMETRIC CHARACTERISICS OF THE DIESEL NOZZLE EXHAUST MICROCHANNEL

In order to obtain automobiles that comply with the increasingly severe pollution standards, as well as to obtain some of them at low costs, a technical-economic approach to the flow of the fuel fluid through the flow holes of the injection nozzles is necessary. Through the effect of hydropolishing the geometric characteristics of the hydraulic flow path, the flow path is modeled, reducing cavitation and achieving high performance. The fluid used is a fluid that has properties close to diesel and has SiC microparticles in suspension (manufacturing costs in in this case they are reduced). The article contains an analysis of the influence of the abrasive flow on the geometric parameters of the nozzle and implicitly on the operation of thermal engines. The results provide a means of identifying parameters that can be compared and evaluated in order to achieve the desired level of hydrodynamic efficiency.