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Food composition database (FCD) provides the nutritional composition of foods. Reliable and up-to date FCD is important in many aspects of nutrition, dietetics, health, food science, biodiversity, plant breeding, food industry, trade and food regulation. FCD has been used extensively in nutrition labelling, nutritional analysis, research, regulation, national food and nutrition policy. The choice of method for the analysis of samples for FCD often depends on detection capability, along with ease of use, speed of analysis and low cost. Sample preparation is the most critical stage in analytical method development. Samples can be prepared using numerous techniques; however it should be applicable for a wide range of analytes and sample matrices. There are quite a number of significant improvements on sample preparation techniques in various food matrices for specific analytes highlighted in the literatures. Improvements on the technology used for the analysis of samples by specific instrumentation could provide an alternative to the analyst to choose for their laboratory requirement. This review provides the reader with an overview of recent techniques that can be used for sample preparation and instrumentation for food analysis which can provide wide options to the analysts in providing data to their FCD.

The nonlinear Schrödinger equation is used to model various phenomena, such as solitons self-focusing effects and rogue waves. In the ocean engineering, the modified nonlinear Schrödinger equation investigates the behavior of water waves, considering the complex interaction of dispersion nonlinearity, and dissipation effects. By introducing fractional derivatives to the model, the M-fractional conformable modified nonlinear Schrödinger equation allows for the investigation of fractional order effects, which can study more accurately the behavior of wave propagation in real-world ocean engineering. The novelty of our research lies in the application of of the M-fractional conformable derivative on the governed equation which represents an advancement in the existing work, which have used nonlinear Schrödinger equations without fractional derivatives. Two powerful techniques: the Jacobi elliptic function method and unified solver method are applied to attain solutions to the M-fractional modified nonlinear Schrödinger equation. The several results, including dark, bright, singular, periodic, and dark-bright soliton solutions are obtained which provide valuable insights into the complex behavior of water waves in ocean engineering. Additionally, 3D and contour graphs have been provided to visually illustrate the impact of the fractional order. We also illustrate these solutions at different values of the fractional order which explain how variations in this parameter affect wave propagation. These findings will contribute to the advancement of ocean engineering techniques, enhancing our ability to design and implement effective solutions for coastal protection, offshore structures, and marine renewable energy systems.

This paper focuses on the estimation of energy consumption of Electric Vehicles (EVs) by means of models derived from traffic flow theory and vehicle locomotion laws. In particular, it proposes a bi-level procedure with the aim to calibrate (or update) the whole parameters of traffic flow models and energy consumption laws by means of Floating Car Data (FCD) and probe vehicle data. The reported models may be part of a procedure for designing and planning transport and energy systems. This aim is to verify if, and in what amount, the existing parameters of the resistances/energy consumptions model calibrated in the literature for Internal Combustion Engines Vehicles (ICEVs) change for EVs, considering the above circular dependency between supply, demand, and supply–demand interaction. The final results concern updated parameters to be used for eco-driving and eco-routing applications for design and a planning transport system adopting a multidisciplinary approach. The focus of this manuscript is on the transport area. Experimental data concern vehicular data extracted from traffic (floating car data and probe vehicle data) and energy consumption data measured for equipped EVs performing trips inside a sub-regional area, located in the Città Metropolitana of Reggio Calabria (Italy). The results of the calibration process are encouraging, as they allow for updating parameters related to energy consumption and energy recovered in terms of EVs obtained from data observed in real conditions. The latter term is relevant in EVs, particularly on urban routes where drivers experience unstable traffic conditions.

Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identification/localization; nevertheless, many FCDs are small or subtle, and difficult to find on routine radiological inspection. We aimed to automatically detect subtle or visually-unidentifiable FCDs by building a classifier based on an optimized cortical surface sampling of combined MRI and PET features. Cortical surfaces of 28 patients with histopathologically-proven FCDs were extracted. Morphology and intensity-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface, and fed to a 2-step (Support Vector Machine and patch-based) classifier. Classifier performance was assessed compared to manual lesion labels. Our classifier using combined feature selections from MRI and PET outperformed both quantitative MRI and multimodal visual analysis in FCD detection (93% vs 82% vs 68%). No false positives were identified in the controls, whereas 3.4% of the vertices outside FCD lesions were also classified to be lesional (“extralesional clusters”). Patients with type I or IIa FCDs displayed a higher prevalence of extralesional clusters at an intermediate distance to the FCD lesions compared to type IIb FCDs (p < 0.05). The former had a correspondingly lower chance of positive surgical outcome (71% vs 91%). Machine learning with multimodal feature sampling can improve FCD detection. The spread of extralesional clusters characterize different FCD subtypes, and may represent structurally or functionally abnormal tissue on a microscopic scale, with implications for surgical outcomes.

In the context of focal and drug-resistant epilepsy, surgical resection of the epileptogenic zone may be the only therapeutic option for reducing or suppressing seizures. In many such patients, intracranial stereo-EEG recordings remain the gold standard for the epilepsy surgery work-up. Assessing the extent of the epileptogenic zone and its organisation is a crucial objective, and requires advanced methods of signal processing. Over the last ten years, considerable efforts have been made to develop signal analysis techniques for characterising the connectivity between spatially distributed regions. The aim of this study was to evaluate the changes in dynamic connectivity pattern under inter-ictal, pre-ictal and ictal conditions using signals derived from stereo-EEG recordings of 10 patients with Taylor-type focal cortical dysplasia. A causal linear multivariate method – partial directed coherence – and indices derived from graph theory were used to characterise the synchronisation property of the lesional zone (corresponding to the epileptogenic zone in our patients) and to distinguish it from other regions involved in ictal activity or not. The results show that a significantly different connectivity pattern (mainly in the gamma band) distinguishes the epileptogenic zone from other cortical regions not only during the ictal event, but also during the inter- and pre-ictal periods. This indicates that the lesional nodes play a leading role in generating and propagating ictal EEG activity by acting as the hubs of the epileptic network originating and sustaining seizures. Our findings also indicate that the cortical regions beyond the dysplasia involved in the ictal activity essentially act as “secondary” generators of synchronous activity. The leading role of the lesional zone may account for the good post-surgical outcome of patients with type II focal cortical dysplasia as resecting the dysplasia removes the epileptogenic zone responsible for seizure organisation. Furthermore, our findings strongly suggest that advanced signal processing techniques aimed at studying synchronisation and characterising brain networks could substantially improve the pre-surgical evaluation of patients with focal epilepsy, even in cases without an associated anatomically detectable lesion. ►Type-II focal cortical dysplasia is a model of drug-resistant epilepsy. ►PDC and graph indexes are appropriate tools to localise the epileptogenic zone. ►The lesional nodes play a leading role in the epileptogenic network. ►An abnormal connectivity characterises the inter-ictal activity of the lesional leads. ►Cortical regions outside dysplasia act as secondary sources of synchronous activity.

Objective: Focal cortical dysplasia (FCD) is the most common pathological cause for pediatric epilepsy, with frontal lobe epilepsy (FLE) being the most prevalent in the pediatric population.We attempted to utilize radiomic and morphological methods on MRI and PET to detect FCD in children with FLE.Methods: 37 children with FLE and 20 controls were included in the primary cohort, and a 5-fold cross-validation was performed. In addition, we validated the performance in an independent site of 12 FLE children. A two-stage experiments including frontal lobe and subregions were employed to detect the lesion area of FCD, incorporating the asymmetric feature between the left and right hemispheres. Specifically, for the radiomics approach, we used gray matter (GM), white matter (WM), GM and WM, and the gray-white matter boundary regions of interest to extract features.Then, we employed an Multi-Layer Perceptron classifier to achieve FCD lesion localization based on both radiomic and morphological methods.The Multi-Layer Perceptron model based on the asymmetric feature exhibited excellent performance both in the frontal lobe and subregions. In the primary cohort and independent site, the radiomics analysis with GM and WM asymmetric features had the highest sensitivity (89.2% and 91.7%) and AUC (98.9% and 99.3%) in frontal lobe. While in the subregions, the GM asymmetric features had the highest sensitivity (85.6% and 79.7%). Furthermore, relying on the highest sensitivity of GM and WM asymmetric features in frontal lobe, when integrated with the subregions results, our approach exhibited overlaps with GM asymmetric features (55.4% and 52.4%), as well as morphological asymmetric features (54.4% and 53.8%), both in the primary cohort and at the independent site.

In the era of educational intelligence, the development of student-oriented personalized learning has become a new trend in educational research. Based on fuzzy cognitive theory, this paper proposes a cognitive diagnosis model for English vocabulary and a personalized test question recommendation model for English vocabulary based on cognitive diagnosis. The cognitive diagnostic model combines the four-parameter logistics model to accurately analyze the learner’s cognitive state, applies the fuzzy CDF assumption to calculate the learner’s knowledgeability level, and employs the fuzzy logic method for cognitive modeling. Assess students’ mastery levels on subjective and objective questions, improve existing recommendation methods that do not adequately consider students’ cognitive levels, and develop a personalized recommendation model for PMF-FCD. We utilized a high school in Yan’an City, Shaanxi Province, China, as a learning location for English vocabulary training. The student’s overall performance on the English vocabulary posttest improved by 14.22 compared with the pre-test, and the mean value of learning attitudes improved by 1.17 compared with the pre-test, with improvements in learning interests, perceptions, and habits. All the strategy dimensions of learning strategies, except the memory strategy dimension, showed significant positive effects after the experiment (p<0.05).

Background We attempted to determine whether the inflammatory pathway HMGB1-TLR4 and the downstream pro-inflammatory cytokines is upregulated in focal cortical dysplasia (FCD) type II and whether there is a correlation between the TLR4 upregulation and disease duration or frequency of epileptic seizures. Methods FCD type II and peri-FCD paired tissues resected from eight children with refractory epilepsy were collected. Through real-time qPCR, Western blot, and co-immunoprecipitation, we examined the differences between FCD lesions and peri-FCD tissues with respect to mRNA expression, protein expression, and protein interaction in HMGB1-TLR4 pathway biomarker and downstream pro-inflammatory factors in whole brain tissue. Then, we used immunofluorescence to examine the difference between FCD lesions and peri-FCD tissues with respect to protein expression and intracellular distribution of HMGB1-TLR4 pathway biomarker in neurons, astrocytes, and oligodendrocytes. Correlation between level of TLR4 expression and disease duration or frequency of epileptic seizures in patients was also analyzed. Results The protein expression levels of TLR4, cytoplasm HMGB1, TLR4/MyD88 complex, ubiquitination of TRAF6, p-IKK, p-IκB-α, p-NF-κB p65, and IL-1β and TNF-α in lesion tissues were significantly higher than those in peri-FCD controls. Total mRNA expression levels of TLR4, IL-1β, and TNF-α in lesion tissues were significantly higher than those in peri-FCD controls, but HMGB1 had no significant change. In neurons and astrocytes inside the lesions, the expression of TLR4 protein was significantly higher than that in peri-FCD tissues, and HMGB1 was mainly expressed in the cytoplasm, while expressed in the nuclei in peri-FCD tissues. But in oligodendrocytes, there was no upregulation of HMGB1-TLR4 pathway in both lesions and peri-FCD tissues. We did not identify the correlation between the level of TLR4 activation and disease duration or frequency of epileptic seizures. Conclusion The HMGB1-TLR4 pathway was upregulated in the neurons and astrocytes inside FCD type II lesions, which led to an increase in the release of downstream pro-inflammatory cytokines. Correlation between the level of TLR4 activation and duration or frequency of epileptic seizures was not identified.

Common surgical treatment options for large focal chondral defects (FCDs) in the knee include microfracturing (MFX) and microdrilling (DRL). Despite numerous studies addressing MFX and DRL of FDCs, no in vivo study has focused on biomechanical analysis of repair cartilage tissue in critical size FCDs with different amounts of holes and penetration depths. Two round FCDs (d=6 mm) were created on the medial femoral condyle in 33 adult merino sheep. All 66 defects were randomly assigned to 1 control or 4 different study groups: 1) MFX1, 3 holes, 2 mm depth; 2) MFX2, 3 holes, 4 mm depth; 3) DRL1, 3 holes, 4 mm depth; and 4) DRL2, 6 holes, 4 mm depth. Animals were followed up for 1 year. Following euthanasia, quantitative optical analysis of defect filling was performed. Biomechanical properties were analysed with microindentation and calculation of the elastic modulus. Quantitative assessment of defect filling showed significantly better results in all treatment groups compared to untreated FCDs in the control group (p<0.001), with the best results for DRL2 (84.2% filling). The elastic modulus of repair cartilage tissue in the DRL1 and DRL2 groups was comparable to the adjacent native hyaline cartilage, while significantly inferior results were identified in both MFX groups (MFX1: p=0.002; MFX2: p<0.001). More defect filling and better biomechanical properties of the repair cartilage tissue were identified for DRL compared to MFX, with the best results for 6 holes and 4 mm of penetration depth. These findings are in contrast to the current clinical practice with MFX as the gold standard and suggest a clinical return to DRL.

Focal cortical dysplasia (FCD) is one of the most common causes of drug-resistant epilepsy. As several studies have revealed, the abnormal functioning of the perisomatic inhibitory system may play a role in the onset of seizures. Therefore, we wanted to investigate whether changes of perisomatic inhibitory inputs are present in FCD. Thus, the input properties of abnormal giant- and control-like principal cells were examined in FCD type IIB patients. Surgical samples were compared to controls from the same cortical regions with short postmortem intervals. For the study, six subjects were selected/each group. The perisomatic inhibitory terminals were quantified in parvalbumin and neuronal nuclei double immunostained sections using a confocal fluorescent microscope. The perisomatic input of giant neurons was extremely abundant, whereas control-like cells of the same samples had sparse inputs. A comparison of pooled data shows that the number of parvalbumin-immunopositive perisomatic terminals contacting principal cells was significantly larger in epileptic cases. The analysis showed some heterogeneity among epileptic samples. However, five out of six cases had significantly increased perisomatic input. Parameters of the control cells were homogenous. The reorganization of the perisomatic inhibitory system may increase the probability of seizure activity and might be a general mechanism of abnormal network activity.