Simplified methodology for testing common rail piezoelectric injectors taking into account reference characteristics

The article presents the methodology of testing Continental/Siemens VDO piezoelectric injectors. To determine the correctness of their operation, the reference characteristics were used, which, due to the lack of guidelines from the manufacturer, constituted the only reference base for the obtained expenses and the intensity of fuel overflows. Simultaneously, the phase of the active experiment was simplified by limiting the number of measuring points, and then estimating the missing data using the Aitken iterative technique. Automation of the calculation process was obtained thanks to the proprietary numerical algorithm, whose formulas were introduced into a standard spreadsheet

Extratemporal functional connectivity impairments at rest are related to memory performance in mesial temporal epilepsy.

Mesial temporal lobe epilepsy (MTLE) is the most frequent form of focal epilepsy. At rest, there is evidence that brain abnormalities in MTLE are not limited to the epileptogenic region, but extend throughout the whole brain. It is also well established that MTLE patients suffer from episodic memory deficits. Thus, we investigated the relation between the functional connectivity seen at rest in fMRI and episodic memory impairments in MTLE. We focused on resting state BOLD activity and evaluated whether functional connectivity (FC) differences emerge from MTL seeds in left and right MTLE groups, compared with healthy controls. Results revealed significant FC reductions in both patient groups, localized in angular gyri, thalami, posterior cingulum and medial frontal cortex. We found that the FC between the left non-pathologic MTL and the medial frontal cortex was positively correlated with the delayed recall score of a non-verbal memory test in right MTLE patients, suggesting potential adaptive changes to preserve this memory function. In contrast, we observed a negative correlation between a verbal memory test and the FC between the left pathologic MTL and posterior cingulum in left MTLE patients, suggesting potential functional maladaptative changes in the pathologic hemisphere. Overall, the present study provides some indication that left MTLE may be more impairing than right MTLE patients to normative functional connectivity. Our data also indicates that the pattern of extra-temporal FC may vary as a function of episodic memory material and each hemisphere\u27s capacity for cognitive reorganization

A test of the role of the medial temporal lobe in single-word decoding.

The degree to which the MTL system contributes to effective language skills is not well delineated. We sought to determine if the MTL plays a role in single-word decoding in healthy, normal skilled readers. The experiment follows from the implications of the dual-process model of single-word decoding, which provides distinct predictions about the nature of MTL involvement. The paradigm utilized word (regular and irregularly spelled words) and pseudoword (phonetically regular) stimuli that differed in their demand for non-lexical as opposed lexical decoding. The data clearly showed that the MTL system was not involved in single word decoding in skilled, native English readers. Neither the hippocampus nor the MTL system as a whole showed significant activation during lexical or non-lexical based decoding. The results provide evidence that lexical and non-lexical decoding are implemented by distinct but overlapping neuroanatomical networks. Non-lexical decoding appeared most uniquely associated with cuneus and fusiform gyrus activation biased toward the left hemisphere. In contrast, lexical decoding appeared associated with right middle frontal and supramarginal, and bilateral cerebellar activation. Both these decoding operations appeared in the context of a shared widespread network of activations including bilateral occipital cortex and superior frontal regions. These activations suggest that the absence of MTL involvement in either lexical or non-lexical decoding appears likely a function of the skilled reading ability of our sample such that whole-word recognition and retrieval processes do not utilize the declarative memory system, in the case of lexical decoding, and require only minimal analysis and recombination of the phonetic elements of a word, in the case of non-lexical decoding

Hippocampal functional connectivity patterns during spatial working memory differ in right versus left temporal lobe epilepsy.

Temporal lobe epilepsy (TLE), affecting the medial temporal lobe, is a disorder that affects not just episodic memory but also working memory (WM). However, the exact nature of hippocampal-related network activity in visuospatial WM remains unclear. To clarify this, we utilized a functional connectivity (FC) methodology to investigate hippocampal network involvement during the encoding phase of a functional magnetic resonance imaging (fMRI) visuospatial WM task in right and left TLE patients. Specifically, we assessed the relation between FC within right and left hippocampus-seeded networks, and patient performance (rate of correct responses) during the encoding phase of a block span WM task. Results revealed that both TLE groups displayed a negative relation between WM performance and FC between the left hippocampus and ipsilateral parahippocampal gyrus. We also found a positive relationship between performance and FC between the left hippocampus seed and the precuneus, in the right TLE group. Lastly, the left TLE specifically demonstrated a negative relationship between performance and FC between both hippocampi and ipsilateral cerebellar clusters. Our findings indicate that right and left TLE groups may develop different patterns of FC to implement visuospatial WM. Indeed, the present result suggests that FC provides a unique means of identifying abnormalities in brain networks, which cannot be discerned at the level of behavioral output through neuropsychological testing. More broadly, our findings demonstrate that FC methods applied to task-based fMRI provide the opportunity to define specific task-related networks

Functional connectivity evidence of cortico-cortico inhibition in temporal lobe epilepsy.

Epileptic seizures can initiate a neural circuit and lead to aberrant neural communication with brain areas outside the epileptogenic region. We focus on interictal activity in focal temporal lobe epilepsy and evaluate functional connectivity (FC) differences that emerge as function of bilateral versus strictly unilateral epileptiform activity. We assess the strength of FC at rest between the ictal and non-ictal temporal lobes, in addition to whole brain connectivity with the ictal temporal lobe. Results revealed strong connectivity between the temporal lobes for both patient groups, but this did not vary as a function of unilateral versus bilateral interictal status. Both the left and right unilateral temporal lobe groups showed significant anti-correlated activity in regions outside the epileptogenic temporal lobe, primarily involving the contralateral (non-ictal/non-pathologic) hemisphere, with precuneus involvement prominent. The bilateral groups did not show this contralateral anti-correlated activity. This anti-correlated connectivity may represent a form of protective and adaptive inhibition, helping to constrain epileptiform activity to the pathologic temporal lobe. The absence of this activity in the bilateral groups may be indicative of flawed inhibitory mechanisms, helping to explain their more widespread epileptiform activity. Our data suggest that the location and build up of epilepsy networks in the brain are not truly random, and are not limited to the formation of strictly epileptogenic networks. Functional networks may develop to take advantage of the regulatory function of structures such as the precuneus to instantiate an anti-correlated network, generating protective cortico-cortico inhibition for the purpose of limiting seizure spread or epileptogenesis

Comparing Polynomials and Neural Network to Modelling Injection Dosages in Modern CI Engines

The article discusses the possibility of using computational methods for modelling the size of the injection doses. Polynomial and artificial intelligence methods were used for prediction. The aim of the research was to analyze whether it is possible to model the operating parameters of the fuel injector without knowing its internal dimensions and tribological associations. The black box method was used to make the model. This method is based on the analysis of input and output parameters and their correlation. The paper proposes a mathematical model determined on the basis of a polynomial and a neural network based on input and output parameters. The above models make it possible to predict the amount of fuel injection doses on the basis of their operating parameters. Modelling was performed in the Matlab environment. Calculating methods could support the diagnosis processes of fuel injectors. Fuel injection characteristic is non-linear. Study shows that it is possible to predict injection characteristic with high matching using polynomial and neural network. That way accelerates fuel injector work parameters research process. Fuel injector test basis on known its work areas. Mathematical modelling can calculate all injection area using few parameters. To modelling fuel injection dosages by neural network have been used back propagation and Levenberg—Marquardt algorithms

The use of neural network algorithms for modeling injection doses of modern fuel injectors

The article presents the possibilities of using artificial intelligence methods to model the injection doses of a modern Common Rail (CR) fuel injector. The presented neural network solution belongs to the experimental models known as black boxes in mechatronics. The backpropagation algorithm and its Levenberg-Marquardt expansion were used for the simulation. The analysis showed that there is a good match between the measurements and the computational model. The proposed solution can be used in the processes of diagnosing not only elements of the injection equipment, but also the internal combustion engine

Comparing Polynomials and Neural Network to Modelling Injection Dosages in Modern CI Engines

The article discusses the possibility of using computational methods for modelling the size of the injection doses. Polynomial and artificial intelligence methods were used for prediction. The aim of the research was to analyze whether it is possible to model the operating parameters of the fuel injector without knowing its internal dimensions and tribological associations. The black box method was used to make the model. This method is based on the analysis of input and output parameters and their correlation. The paper proposes a mathematical model determined on the basis of a polynomial and a neural network based on input and output parameters. The above models make it possible to predict the amount of fuel injection doses on the basis of their operating parameters. Modelling was performed in the Matlab environment. Calculating methods could support the diagnosis processes of fuel injectors. Fuel injection characteristic is non-linear. Study shows that it is possible to predict injection characteristic with high matching using polynomial and neural network. That way accelerates fuel injector work parameters research process. Fuel injector test basis on known its work areas. Mathematical modelling can calculate all injection area using few parameters. To modelling fuel injection dosages by neural network have been used back propagation and Levenberg—Marquardt algorithms

Model Issues Regarding Modification of Fuel Injector Components to Improve the Injection Parameters of a Modern Compression Ignition Engine Powered by Biofuel

This article presents a theoretical analysis of the use of spiral-elliptical ducts in the atomizer of a modern fuel injector. The parameters of the injected fuel stream can be divided into quantitative and qualitative. The quantitative parameter is the injection dose amount, and the qualitative parameter is characterized by the stream of injected fuel (width, atomization, opening angle, and range). The purpose of atomizer modification is to cause additional flow turbulence, which may affect the stream parameters and improve the combustion process of the combustible mixture in a diesel engine. The spiral-elliptical ducts discussed here could be used in engines powered by vegetable fuels. The stream of such fuels has worse quality parameters than conventional fuels, due to their higher viscosity and density. The proposal to use spiral-elliptical ducts is an innovative idea for diesel engines