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An analytic method is proposed to compute the price-reserve offer curve at the consumer level in hierarchical direct load control. The convexification of the consumer reserve provision is examined, and the analytic expression of the optimal solution within each critical region is derived. Then, based on multi-parametric programming, a combinatorial enumeration method in conjunction with efficient reduction and pruning strategy is proposed to compute the optimal response of consumers in the whole price space. Numerical tests along with an application example in the bi-level aggregator pricing problem demonstrate the merit of this method.

The recently proposed q-rung orthopair fuzzy set (q-ROFS) whose main feature is that the qth power of membership degree (MD) and the qth power of non-membership degree (NMD) is equal to or less than 1, is a powerful tool to describe uncertainty. The major contribution of this paper lies to investigate power point average (PPA) aggregation operators with q-rung orthopair fuzzy information based on Frank t-conorm and t-norm. Since the existing power average (PA) operators all rely on the traditional distance measures to measure support degree between the input values, it cannot reflect decision makers’ attitude. In response, this paper introduces firstly a series of distance measures for q-rung orthopair fuzzy numbers (q-ROFNs) based on point operators, from which the corresponding support measures can be obtained. Secondly, based on the proposed point distance measures, new Frank power point average aggregation operators are proposed to aggregate q-rung orthopair fuzzy information. Finally, a novel multiple attribute decision making (MADM) technique is presented based on the proposed Frank power point average aggregation operators. The developed MADM method not only can get more objective information, but also avoid the influence of unduly high or low attribute values on the decision result, providing a new way for decision makers (DMs) under q-rung orthopair fuzzy environment.

The low yield and poor fuel properties of bio-oil have made the pyrolysis production process uneconomic and also limited bio-oil usage. Proper manipulation of key pyrolysis variables is paramount in order to produce high-quality bio-oil that requires less upgrading. In this research, the pyrolysis of pig hair was carried out in a fixed-bed reactor using a calcium oxide catalyst derived from calcination of turtle shells. In the pyrolysis process, the influence of three variables—temperature, heating rate and catalyst weight—on two responses—bio-oil yield and its higher heating value (HHV)—were investigated using Response Surface Methodology. A second-order regression-model equation was obtained for each response. The optimum yield of the bio-oil and its HHV were obtained as 51.03% and 21.87 mJ/kg, respectively, at 545oC, 45.17oC/min and 2.504 g of pyrolysis temperature, heating rate and catalyst weight, respectively. The high R2 values of 0.9859 and 0.9527, respectively, obtained for the bio-oil yield and its HHV models using analysis of variance revealed that the models can adequately predict the bio-oil yield and its HHV from the pyrolysis process.

Background Misdiagnosis of multiple sclerosis (MS) and neuromyelitis optica (NMO) may delay the treatment, resulting in poor prognosis. However, the precise identification of these two diseases is still challenging in clinical practice. We aimed to evaluate the value of quantitative radiomic features extracted from the brain white matter lesions for differential diagnosis of MS and NMO. Methods We recruited 116 CNS demyelinating patients including 78 MS, and 38 NMO. Three neuroradiologists performed visual differential diagnosis based on brain MRI for comparison purpose. A multi-level scheme was designed to harness the selection of discriminative and stable radiomics features extracted from brain while mater lesions in T1-MPRAGE, T2 sequences and clinical factors. Based on the imaging phenotype composed of the selected radiomic and clinical features, Multi-parametric Multivariate Random Forest (MM-RF) model was constructed and verified with both 10-fold cross-validation and independent testing. Result interpretation was provided to build trust in diagnostic decisions. Results Eighty-six patients were randomly selected to form the training set while the rest 30 patients for independent testing. On the training set, our MM-RF model achieved accuracy 0.849 and AUC 0.826 in 10-fold cross-validation, which were significantly higher than clinical visual analysis (0.709 and 0.683, p p of all Conclusions Multi-parametric radiomic features have potential as practical quantitative imaging biomarkers for differentiating MS from NMO.

PURPOSE To introduce a gradient echo (GRE) -based method, namely MULTIPLEX, for single-scan 3D multi-parametric MRI with high resolution, signal-to-noise ratio (SNR), accuracy, efficiency, and acquisition flexibility. THEORY With a comprehensive design with dual-repetition time (TR), dual flip angle (FA), multi-echo, and optional flow modulation features, the MULTIPLEX signals contain information on radiofrequency (RF) B1t fields, proton density, T1 , susceptibility and blood flows, facilitating multiple qualitative images and parametric maps. METHODS MULTIPLEX was evaluated on system phantom and human brains, via visual inspection for image contrasts and quality or quantitative evaluation via simulation, phantom scans and literature comparison. Region-of-interest (ROI) analysis was performed on parametric maps of the system phantom and brain scans, extracting the mean and SD of the T1 , T2∗ , proton density (PD), and/or quantitative susceptibility mapping (QSM) values for comparison with reference values or literature. RESULTS One MULTIPLEX scan offers multiple sets of images, including but not limited to: composited PDW/T1 W/ T2∗ W, aT1 W, SWI, MRA (optional), B1t map, T1 map, T2∗ / R2∗ maps, PD map, and QSM. The quantitative error of phantom T1 , T2∗ and PD mapping were

Multi-parametric photoacoustic microscopy (PAM) has emerged as a promising new technique for high-resolution quantification of hemodynamics and oxygen metabolism in the mouse brain. In this work, we have extended the scope of multi-parametric PAM to longitudinal, cortex-wide, awake-brain imaging with the use of a long-lifetime (24 weeks), wide-field (5 × 7 mm2), light-weight (2 g), dual-transparency ( i.e., light and ultrasound) cranial window. Cerebrovascular responses to the window installation were examined in vivo, showing a complete recovery in 18 days. In the 22-week monitoring after the recovery, no dura thickening, skull regrowth, or changes in cerebrovascular structure and function were observed. The promise of this technique was demonstrated by monitoring vascular and metabolic responses of the awake mouse brain to ischemic stroke throughout the acute, subacute, and chronic stages. Side-by-side comparison of the responses in the ipsilateral (injury) and contralateral (control) cortices shows that despite an early recovery of cerebral blood flow and an increase in microvessel density, a long-lasting deficit in cerebral oxygen metabolism was observed throughout the chronic stage in the injured cortex, part of which proceeded to infarction. This longitudinal, functional-metabolic imaging technique opens new opportunities to study the chronic progression and therapeutic responses of neurovascular diseases.

The direct hydrogenation of CO 2 to higher alcohols has the potential to turn the main contributor of global warming into a valuable feedstock. However, for this technology to become attractive, more efficient and, especially, selective catalysts are required. Here we present a high throughput study on the influence of different promoters on the CO 2 hydrogenation performance of Rh‐SiO 2 catalysts. Fe and K promoters were found to improve ethanol selectivity at the expense of undesired CH 4 . The best‐performing catalyst, with a composition 2 wt.% K, 20 wt.% Fe, and 5 wt.% Rh, displays an EtOH selectivity of 16% at CO 2 conversion level of 18.4% and CH 4 selectivity of 46%. The combination of different characterization techniques and catalyst screening allowed us to unravel the role of each catalyst component in this complex reaction mechanism.

The groundwater quality of the Indus basin of Punjab, India, is a serious concern due to the existence of toxic contaminants. Although, this contamination has been documented in some studies, some ...

We construct multi-parametric rational solutions to the KdV equation. For this, we use solutions in terms of exponentials depending on several parameters and take a limit when one of these parameters goes to 0. Here we present degenerate rational solutions and give a result without the presence of a limit as a quotient of polynomials depending on 3N parameters. We give the explicit expressions of some of these rational solutions.

BackgroundTissue clearing technologies have enabled remarkable advancements for in situ characterization of tissues and exploration of the three-dimensional (3D) relationships between cells, however, these studies have predominantly been performed in non-human tissues and correlative assessment with clinical imaging has yet to be explored. We sought to evaluate the feasibility of tissue clearing technologies for3Dimaging of intact human prostate and the mapping of structurally and molecularly preserved pathology data with multi-parametric volumetric MR imaging (mpMRI).MethodsWhole-mount prostates were processed with either hydrogel-based CLARITY or solvent-based iDISCO. The samples were stained with a nuclear dye or fluorescently labeled with antibodies against androgen receptor, alpha-methylacyl coenzyme-A racemase, or p63, and then imaged with 3D confocal microscopy. The apparent diffusion coefficientand Ktrans maps were computed from preoperative mpMRI.ResultsQuantitative analysis of cleared normal and tumor prostate tissue volumes displayed differences in 3D tissue architecture, marker-specific cell staining, and cell densities that were significantly correlated with mpMRI measurements in this initial, pilot cohort.Conclusions3D imaging of human prostate volumes following tissue clearing is a feasible technique for quantitative radiology-pathology correlation analysis with mpMRI and provides an opportunity to explore functional relationships between cellular structures and cross-sectional clinical imaging.

Over the last decade, we have seen the emergence of tissue-based genomic prognostic markers that can be used for decision-making regarding the need for treatment. This review provides an up-to-date summary of the relevant literature surrounding these markers with a discussion of the relevant strength and limitations. We performed a literature search of tissue-based genomic prognostic markers and selected those that were currently available for clinical use. We selected the following markers for further review: Decipher (Decipher Bioscience), Polaris (Myriad), Genome Prostate Score (Oncotype Dx), and Promark. We selected the initial validation study for each marker along with other validation studies in independent cohorts. Furthermore, we selected available clinical utility studies or studies combining multi parametric MRI. In this article, we provide an in-depth review of four commercially available biomarkers and discuss the current literature surrounding these markers, including the benefits and limitations of their use. We found that each of these markers has evidence supporting their role as an independent predictor of relevant prostate cancer endpoints, which can be helpful for clinical decision-making. However, issues related to heterogeneity and a lack of prospective randomized studies supporting their utility are limitations. Evidence appears to suggest that MRI and genomic risk assessment maybe complementary. Although these markers can help in improved risk stratification of patients eligible for AS, more prospective studies with head to head comparison between markers are needed to elucidate the true potential of these markers in AS.

Objective: To propose Multi-parametric Deep Neural Network (MDNN) for modeling the impact of climate changes, multiple parameters related to the weather and soil for accurate crop yield prediction. Methods: In MDNN, a measure called Growing-Degree Day (GDD) is introduced for measuring the overall effect of weather conditions related to the crop yield. One of the key elements in MDNN is the neuron’s layer-wise activation function. In order to enhance the crop yield predictive performance, a leaky rectified linear unit is used in the activation units of MDNN. For the analysis of performance of DNN and MDNN, data about weather, crop and soil are collected from http://www.ccafs-climate.org/climatewizard/, https://data.world/thatzprem/agriculture-india and https://data.gov.in/search/site?query=soil respectively. From the collected data, 60000 records are used for training and 40,000 records are used for testing. Findings: By considering multiple parameters of climate and the effect of weather on crop yield, the accuracy of MDNN is improved for predicting the crop yield. The effectiveness of MDNN is tested and compared with DNN for different types of crops. The MDNN achieves 91.84% of mean accuracy for five different crops compared to the DNN classification. Novelty: This proposed work tries to predict the crop yield more accurately by analyzing the climate, weather and soil parameters. The MDNN considerably improves statistical efficiency over typical DNN by using previous knowledge about important phenomena and functional forms relating them to the crop yield. Keywords: Crop yield prediction; machine learning; DNN; climatic changes; soil parameters; growing degree-day

The demarcation of linear geomorphological features due to fracture systems, underlying or exposed faults, drainage lines etc. from satellite images has been one of the most widely used application...

PurposeThe main objective of this experimental work is to analyze and measure the form tolerances namely flatness and squareness while machining a meso deep hole in EDM on Inconel-718 material plate.Design/methodology/approachThe experiments were performed on 15 amps rated SPARKONIX-EDM as per DOE (design of experiments). Kerosene was used as a dielectric along with constant pressure of 0.2 kg/cm2 for all trial runs. The currents Ton and Toff were selected as process constraints to conduct experimental trials. The MRR, EWR, machining time and form tolerances were considered as output responses. The experimental outcomes were optimized by hybrid optimization using Taguchi and GRA (grey relational analysis) method.FindingsThe EDM process parameters for Ni-based super alloy namely Inconel-718 had optimized by using GRA method coupled with Taguchi method. The optimum solution has been calculated for MRR, EWR, machining time and form tolerances namely squareness and flatness. The optimized parameters for the output responses in EDM process are Peak current (Ip) 12 Amps, 400 µs Ton (pulse on time) and 10 µs Toff (pulse off time). An attempt had also been made to attain Max. and Min. Evaluation of MRR and form tolerances, respectively. The attained optimum outcomes had also been examined through a real experiment and established to be satisfactory.Practical implicationsThis article will facilitate the defense, aerospace and EDM industries to improve their productivity with closer tolerances.Originality/valueThe optimized parameters by multi-parametric optimization showed the considerable improvement in the process and will facilitate the defense, aerospace and EDM industries to improve their productivity with closer tolerances.

We investigate the surface deformation pattern of GPS station at MPGO Ghuttu (GHUT) to find out the cause of anomalous behavior in the continuous GPS time series. Seven years (2007-2013) of GPS data has been analyzed using GAMIT/GLOBK software and generated the daily position time series. The horizontal translational motion at GHUT is 43.7 ± 1 mm/yr at an angle of 41°± 3° towards NE, while for the IGS station at LHAZ, the motion is 49.4 ±1 mm/yr at 18 ± 2.5° towards NEE. The estimated velocity at GHUT station with respect to IISC is 12 ± 1 mm/yr towards SW. Besides, we have also examined anomalous changes in the time series of GHUT before, after and during the occurrences of local earthquakes by considering the empirical strain radius; such that, a possible relationship between the strain radius and the occurrences of earthquakes have been explored. We considered seven local earthquakes on the basis of Dobrovolsky strain radius condition having magnitude from 4.5 to 5.7, which occurred from 2007 to 2011. Results show irrespective of the station strain radius, pre-seismic surface deformational anomalies are observed roughly 70 to 80 days before the occurrence of a Moderate or higher magnitude events. This has been observed for the cases of those events originated from the Uttarakashi and the Chamoli seismic zones in the Garhwal and Kumaun Himalaya. Occurrences of short (< 100 days) and long (two years) inter-seismic events in the Garhwal region plausibly regulating and diffusing the regional strain accumulation.

Conventional staging for bladder cancer involves CT and TURBT, and is thought to understage up to fifty-percent of T1 tumours. This report details the case of a 64-year-old male who whilst on cystoscopic surveillance for high grade bladder cancer, underwent a multi-parametric MRI Bladder due to clinical suspicion of occult muscle invasive disease. Despite minimal urothelial changes at cystoscopy, MRI demonstrated a well-defined T3 lesion. The patient proceeded to radical cystectomy and final pathology verified the MRI findings. The role of MRI in bladder cancer is yet to be defined but should be considered if clinical suspicion for understaging exists.

To investigate a variety of magnetic resonance imaging (MRI) quantitative metrics, which reflect different aspects of microstructural damage in deep gray matter (dGM) regions and white matter T2 lesions in patients with relapsing-remitting multiple sclerosis (RRMS), and to determine the level of pathological interconnection between these two entities as well as their association with clinical disability. We recruited thirty RRMS patients along with thirty age-matched healthy controls (HCs). Both groups were scanned at 3 T MRI using 3D high-resolution T1-, T2-, and T2*-weighted, magnetization transfer (MT)–prepared gradient echo for MT ratio (MTR) mapping, and eight repeats of T1-weighted images acquired at different inversion times to create T1 maps. dGM structures were segmented from T1-weighted images using FreeSurfer, WM-T2 lesions were extracted from T2-weighted images, and iron maps were calculated from the phase part of the T2*-weighted sequence. Extracted dGM MRI indices were compared between both groups. In the RRMS group, dGM MRI indices were correlated with those of WM-T2 lesions, expanded disability status scale, and disease duration. dGM volumetric metrics of RRMS patients were significantly (p < 0.01) smaller than those of HCs and showed a significant moderate association with lesions’ load (p < 0.05) and lesions’ iron concentration (p < 0.01). dGM MTRs of RRMS patients were significantly (p < 0.01) smaller than those of HCs and showed a significant (p < 0.01) moderate correlation with lesion T1 times. While T1 changes in some dGM regions of RRMS patients associated weakly with those of T2 lesions, dGM iron concentration did not show any association with any of lesions’ metrics. Furthermore, lesions’ MTR changes did not show any association with any dGM metrics. Most dGM metrics did not show any correlation with disease severity. Contrarily, most lesions’ metrics showed weak association with disease severity. dGM changes occur in a non-uniform pattern and, almost, do not link directly to MS disease severity. Contrarily, most WM-T2 lesions’ metrics tend to correlate with MS disease severity better than those of dGM. • Deep gray matter (dGM) structures are very much involved in the MS disease process and quite substantial neurodegeneration is undergone during the relapsing-remitting phase of the MS disease. • Deep gray matter (dGM) quantitative changes occur in a non-uniform and non-linked pattern and, except for CN’s iron deposition, do not directly associate with the MS disease severity. • Most white matter T2 lesions’ metrics tend to correlate with MS disease severity better than those of dGM structures.

International audience; From elementary exponential functions which depend on several parameters, we construct multi-parametric solutions to the Boussinesq equation. When we perform a passage to the limit when one of these parameters goes to0, we get rational solutions as a quotient of apolynomial of degree N(N+1)−2inx and Boussinesq equation,KadomtsevPetviashviliequation,Rational solutionst, by a polynomial of degree N(N+1)in x and t for each positive integer N depending on 3N real parameters. We restrict ourself to give the explicit expressions of these rational solutions fo rN=1 until N=3to shortened thepaper. We easily deduce the corresponding explicit rational solutions to the Kadomtsev Petviashvili equation for the same orders from 1 to 3.

Microvascular invasion (mVI) is the most significant independent predictor of recurrence for hepatocellular carcinoma (HCC), but its pre-operative assessment is challenging. In this study, we investigate the use of multi-parametric MRI radiomics to predict mVI status before surgery. We retrospectively collected pre-operative multi-parametric liver MRI scans for 99 patients who were diagnosed with HCC. These patients received surgery and pathology-confirmed diagnosis of mVI. We extracted radiomics features from manually segmented HCC regions and built machine learning classifiers to predict mVI status. We compared the performance of such classifiers when built on five MRI sequences used both individually and combined. We investigated the effects of using features extracted from the tumor region only, the peritumoral marginal region only, and the combination of the two. We used the area under the receiver operating characteristic curve (AUC) and accuracy as performance metrics. By combining features extracted from multiple MRI sequences, AUCs are 86.69%, 84.62%, and 84.19% when features are extracted from the tumor only, the peritumoral region only, and the combination of the two, respectively. For tumor-extracted features, the T2 sequence (AUC = 80.84%) and portal venous sequence (AUC = 79.22%) outperform other MRI sequences in single-sequence-based models and their combination yields the highest AUC of 86.69% for mVI status prediction. Our results show promise in predicting mVI from pre-operative liver MRI scans and indicate that information from multi-parametric MRI sequences is complementary in identifying mVI.

Background Acute necrotizing encephalopathy of children (ANEC) is a rare fulminant type of acute encephalopathy that mainly occurs in children with a characteristic clinico-radiological pattern. It is commonly preceded by viral infections. The condition carries a poor prognosis with high morbidity and mortality rates. We highlight the relationship between diagnostic multi-parametric magnetic resonance imaging (MRI) findings and correlate them with the clinical outcome of children with ANEC by enrollment of MRI scoring. Results The thalami were involved in all 30 patients, brain stem in 80%, basal ganglia (13.3%), cerebral white matter (WM) in 73%, and cerebellar WM in 33%. Hemorrhage was present in 86.7% patients, edema 80%, and necrosis in 13.3%. We found that the patients having the highest MRI scores were in the poor outcome category; whereas the patients with lower MR score (1 or 2) had better outcomes. Statistically positive correlation (r= 0.1198) was found between the multi-parametric MR score and the outcome category. Conclusion An extended multi-parametric MRI should be performed in ANEC, allowing early detection and scoring of the disease for better prognosis. There is a positive correlation between the clinical outcome and the MR scoring.

In this paper, a multi-parametric analysis modelling for an ultra-wideband (UWB) antenna using artificial neural networks is proposed to predict both the UWB impedance bandwidth and multi-band notc...

Purpose Quantitative T1 , T2 , T2 *, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1 , T2 , T2 *, and FF mapping from a single ~14 s breath-hold scan. Methods A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5-15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1 , T2 , T2 *, and FF simultaneously. The nine-echo time-series are reconstructed using a low-rank tensor constrained reconstruction and used to fit T2 *, B0 and to separate the water and fat signals. Water- and fat-specific T1 , T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1 /T2 phantom, a water-fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. Results The proposed water T1 , water T2 , T2 *, and FF maps in phantoms showed high coefficients of determination (r2 > 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1 , T2 , T2 *, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, -7.1 ms, -1.4 ms, and 0.63% when compared to conventional methods. Conclusion A nine-echo liver MRF sequence allows for quantitative multi-parametric liver tissue characterization in a single breath-hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.

There is increasing evidence to suggest the value of bi-parametric prostate MRI to replace multi-parametric MRI, which includes the dynamic contrast enhancement (DCE) sequence. In this review, we discuss the value of DCE in select scenarios, specifically in resolving equivocal cases, improving the diagnostic accuracy in the inexperienced reader, rescuing exams in the settings of failed T2W and DWI, detecting biochemical recurrence, while imposing minimal to no risk to the patient with respect to IV gadolinium use, specifically group II agents.

BACKGROUND: To compare the diagnostic performance of (68)Ga-prostate-specific membrane antigen positron emission tomography/computed tomography ((68)Ga-PSMA PET/CT) with multi-parametric magnetic resonance imaging (mpMRI) on extracapsular extension (ECE) and seminal vesicle invasion (SVI) in primary prostate cancer and its impact on therapeutic decisions. METHODS: We retrospectively enrolled 54 patients with both PET/CT and mpMRI before radical prostatectomy. Diagnostic performance of mpMRI, PET/CT and their combination (com-MRI/PET) on ECE and SVI on a patient basis were analyzed. The impact of additional PET/CT scanning on therapeutic decisions were presented. RESULTS: Among the 54 patients, 17 had tumor limited in the prostate gland, 25 only had ECE and 12 patients had both SVI and ECE on pathology. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of ECE were 54%, 94%, 95%, 48% on mpMRI, 78%, 94%, 97%, 67% on PET/CT and 83%, 88%, 94%, 71% on com-MRI/PET. Both PET/CT and com-MRI/PET had a higher sensitivity than mpMRI on ECE diagnosis (78% vs. 54%, P

Purpose To assess arterial spin labelling (ASL) perfusion and diffusion MR imaging (DWI) in the differentiation of grade II from grade III gliomas. Material and methods A prospective cohort study was done on 36 patients (20 male and 16 female) with diffuse gliomas, who underwent ASL and DWI. Diffuse gliomas were classified into grade II and grade III. Calculation of tumoural blood flow (TBF) and apparent diffusion coefficient (ADC) of the tumoral and peritumoural regions was made. The ROC curve was drawn to differentiate grade II from grade III gliomas. Results There was a significant difference in TBF of tumoural and peritumoural regions of grade II and III gliomas (p = 0.02 and p =0.001, respectively). Selection of 26.1 and 14.8 ml/100 g/min as the cut-off for TBF of tumoural and peritumoural regions differentiated between both groups with area under curve (AUC) of 0.69 and 0.957, and accuracy of 77.8% and 88.9%, respectively. There was small but significant difference in the ADC of tumoural and peritumoural regions between grade II and III gliomas (p = 0.02 for both). The selection of 1.06 and 1.36 × 10-3 mm2/s as the cut-off of ADC of tumoural and peritumoural regions was made, to differentiate grade II from III with AUC of 0.701 and 0.748, and accuracy of 80.6% and 80.6%, respectively. Combined TBF and ADC of tumoural regions revealed an AUC of 0.808 and accuracy of 72.7%. Combined TBF and ADC for peritumoural regions revealed an AUC of 0.96 and accuracy of 94.4%. Conclusion TBF and ADC of tumoural and peritumoural regions are accurate non-invasive methods of differentiation of grade II from grade III gliomas.

In the course of this project we were able to develop a wastewater treatment method, column filtration, which turned out to be effective, affordable, and easily implementable. We tested filtration/adsorption process on a mixture of three dyes, methylene blue (MB), crystal violet (CV), and methyl orange (MO) on a column 50 cm of height and 5 cm in diameter. The column material consisted of equal amounts of walnut shells powder (WSP), corn cob powder calcined (CCPC), and pyrophyllite (PY) was proved to be more efficient. The aim of the present study was to optimize and standardize the operational and experimental parameters of the column. A number of tests were carried out to do this by changing the particle size of the adsorbent materials, the percolation debit of the filtrate and the height of the filter bed. The examination by UV-visible spectrometry shows that the removal percentage by 99% was carried out by the diameter of 120 μm predominantly with percolation debit of the filtrate of 50 mL min−1 and the height of column bed of 4.5 cm. When the materials having macroscopic porous structure with a very small grain diameter were used, of small-sized dyes into the filtering medium without being trapped. On the other hand, it is noticed that the efficiency of the adsorption by filtration increases with the increase in the height of the filter bed and decreases with the increase of both the percolation debit and particle size of the adsorbents.

The apparent resistivity imaging at multiparametric geophysical observatory (MPGO), Ouguri Hills, Tezpur was carried out since 31st August, 2016 for fixed interval time of 3 days to investigate precursory signature prior to earthquake events. Anomalies in apparent resistivity prior to earthquake events are observed. The anomalies are not influenced by the rainfall activity in the region during the investigation period. We adopt Weibull distribution technique with observed apparent resistivity data to look for and revalidate the observations. The Weibull parameters, i.e. K and m are estimated to be 0.26 and 1.04, respectively. No precise relation between magnitude and earthquake precursory time is found. Simultaneously, an attempt has been made to establish a relation between the earthquake magnitude (M) and precursory time (T) and a relation between the earthquake precursory time (T) and distance of the earthquake (Δ) from the observation point. Weibull probability distribution indicate the probability of an earthquake occurrence exceeds the measure up to 80% (9 days) after the precursory signal is observed. A comparison of probability analysis ascertains a mean precursory time and its standard deviation.

Objective: Fluorescence molecular imaging (FMI) has emerged as a promising tool for surgical guidance in oncology, with one of the few remaining challenges being the ability to offer quality control and data referencing. This paper investigates the use of a novel composite phantom to correct and benchmark FMI systems. Methods: This paper extends on previous work by describing a phantom design that can provide a more complete assessment of FMI systems through quantification of dynamic range and determination of spatial illumination patterns for both reflectance and fluorescence imaging. Various performance metrics are combined into a robust and descriptive "system benchmarking score," enabling not only the comprehensive comparison of different systems, but also for the first time, correction of the acquired data. Results: We show that systems developed for targeted fluorescence imaging can achieve benchmarking scores of up to 70 & x0025;, while clinically available systems optimized for indocyanine green are limited to 50 & x0025;, mostly due to greater leakage of ambient and excitation illumination and lower resolution. The image uniformity can also be approximated and employed for image flat-fielding, an important milestone toward data referencing. In addition, we demonstrate composite phantom use in assessing the performance of a surgical microscope and of a raster-scan imaging system. Conclusion: Our results suggest that the new phantom has the potential to support high-fidelity FMI through benchmarking and image correction. Significance: Standardization of the FMI is a necessary process for establishing good imaging practices in clinical environments and for enabling high-fidelity imaging across patients and multi-center imaging studies.

Задачи геометрического моделирования многопараметрических технологических систем и процессов актуальны в связи с возможностью моделирования классов подобных систем. Целью статьи является описание метода построения геометрических моделей для решения обратных задач управления технологическими процессами. Основой построения моделей являются экспериментальные данные. Результатом моделирования является множество переменных одномерных сплайнов, образующих нелинейный каркас гиперповерхности взаимосвязи параметров процесса. Предлагаемые метод, алгоритмы и программа визуализации использованы при исследовании свойств перо-пуховых пакетов швейных изделий и технологических процессов их изготовления. В результате получены новые научно обоснованные параметры пакетов теплозащитной одежды с несвязным наполнителем, которые могут быть использованы в проектировании одежды и при выборе режимов работы дозаторов.

[EN] Purpose: To systematically review evidence regarding the association of multi-parametric biomarkers with clinical outcomes and their capacity to explain relevant subcompartments of gliomas. Materials and Methods: Scopus database was searched for original journal papers from January 1st, 2007 to February 20th , 2017 according to PRISMA. Four hundred forty-nine abstracts of papers were reviewed and scored independently by two out of six authors. Based on those papers we analyzed associations between biomarkers, subcompartments within the tumor lesion, and clinical outcomes. From all the articles analyzed, the twenty-seven papers with the highest scores were highlighted to represent the evidence about MR imaging biomarkers associated with clinical outcomes. Similarly, eighteen studies defining subcompartments within the tumor region were also highlighted to represent the evidence of MR imaging biomarkers. Their reports were critically appraised according to the QUADAS-2 criteria. Results: It has been demonstrated that multi-parametric biomarkers are prepared for surrogating diagnosis, grading, segmentation, overall survival, progression-free survival, recurrence, molecular profiling and response to treatment in gliomas. Quantifications and radiomics features obtained from morphological exams (T1, T2, FLAIR, T1c), PWI (including DSC and DCE), diffusion (DWI, DTI) and chemical shift imaging (CSI) are the preferred MR biomarkers associated to clinical outcomes. Subcompartments relative to the peritumoral region, invasion, infiltration, proliferation, mass effect and pseudo flush, relapse compartments, gross tumor volumes, and high-risk regions have been defined to characterize the heterogeneity. For the majority of pairwise cooccurrences, we found no evidence to assert that observed co-occurrences were significantly different from their expected co-occurrences (Binomial test with False Discovery Rate correction, alpha=0.05). The co-occurrence among terms in the studied papers was found to be driven by their individual prevalence and trends in the literature. Conclusion: Combinations of MR imaging biomarkers from morphological, PWI, DWI and CSI exams have demonstrated their capability to predict clinical outcomes in different management moments of gliomas. Whereas morphologic-derived compartments have been mostly studied during the last ten years, new multi-parametric MRI approaches have also been proposed to discover specific subcompartments of the tumors. MR biomarkers from those subcompartments show the local behavior within the heterogeneous tumor and may quantify the prognosis and response to treatment of gliomas., This work was supported by the Spanish Ministry for Investigation, Development and Innovation project with identification number DPI2016-80054-R.

This project aims to demonstrate a multi-parametric method of hospital technology comparison. The main goal was to develop a method to assist the clinical and hospital engineering team, in the process of acquisition and incorporation of medical-hospital equipment, to be used as a tool in the comparison stage of brand options and models of available equipment in the market. The method is composed by groups of criteria or characteristics that can be evaluate referring to the technologies to be compared. This method was applied to compare autoclaves and disinfecting machines that would be purchased to install in a Material Central and Sterilization (CME) in a hospital in the south of Brazil. As a result, it was obtained the classifications with the final scoring referring to each brand and model of technology. It also contributed significantly to assist the choice definition of the equipment, considering the hospital and technology profile, as well as the requirements and expectations of the multi-professional technical group of evaluators and users.

In neuroscience, a deep understanding of communication mechanisms at the cellular level is of paramount importance, since their dysfunction determines the onset of several diseases. The development of innovative sensors devoted to the investigation of both chemical and electrical signals it is therefore essential to improve the outcome of standard trials and to define novel methodologies. Here we report on the fabrication and the characterization of multi-functional micrographite patterned diamond multi-electrode arrays. These sensors are obtained by means of a three-dimensional patterning process of single-crystal diamond substrates by means of MeV ion-beam-based lithography, which allows the direct fabrication of graphitic micro-channels embedded within the bulk of the electrically insulating diamond matrix. Proof-of-concept in vitro experiments on cultured neurons and cardiac tissue were performed, in which quantal secretory events were amperometrically recorded from dopaminergic neurons, while potentiometric measurements of action potential generation were collected from both hippocampal neuronal networks and intact sinoatrial nodes. These achievements represent the demonstration of the applicability of an all-carbon hybrid graphite/diamond device for the multi parametric detection of chemical and electrical signals, thus representing a fundamental step for the simultaneous in vitro measurement of the two types of signals from the same biological sample.

Purpose To evaluate the utility of multi-parametric magnetic resonance imaging (MP-MRI), including dynamic contrast-enhanced MRI and diffusion-weighted MRI, for monitoring tumor tissue changes after volumetric-modulated arc radiotherapy in localized prostate cancer (PCa), and to compare the radiotherapy induced tumor tissue changes between conventional, moderate and extreme hypofractionated groups. Furthermore, we aimed to evaluate if follow-up by MRI has an incremental value compared to the standard care by prostate-specific antigen (PSA) serum level measurement. Materials and methods Fifty-five men (mean age: 70 ± 5 [SD] years; range: 60–79 years) with biopsy-proven PCa underwent MRI examination before radiotherapy, and at 3 and 12 months after radiotherapy. Pharmacokinetic analysis post-processing platform with dedicated software (Tissue 4D) was used to generate colorized parametric maps of enhancing tumors. The volume transfer constant (Ktrans), reflux constant (Kep), and initial area under curve (iAUC) were calculated from the tumors. Tumor apparent diffusion coefficient (ADC) value was measured on the ADC map. The patients were allocated into three radiotherapy groups: 17 conventional (39 × 2 Gy), 16 moderate (20 × 3 Gy) and 22 extreme hypofractionated (5 × 7.25 Gy) regimen. Results Sixty lesions were detected in the prostates of the 55 patients. Follow-up MRI showed decreases in tumor size and degree of enhancement. Ktrans, Kep, and iAUC all decreased at 3 months (P Conclusion MP-MRI is a reliable tool for lesion detection and follow-up, providing both qualitative and quantitative data.

In this research, general regression neural network (GRNN), Hammerstein-wiener (HW) and non-linear autoregressive with exogenous (NARX) neural network, least square support vector machine (LSSVM) models were employed for multi-parametric (Hardness (mg/L), turbidity (Turb) (μs/cm), pH and suspended solid (SS) (mg/L)) modeling of Tamburawa water treatment plant (TWTP) at Kano, Nigeria. The weekly data from the TWTP were used and the predictive models were evaluated based on several numerical indicators. Four different non-linear ensemble techniques (GRNN-E, HW-E, NARX-E, and LSSVM-E) were subsequently employed. The comparison of the results of modeling showed that HW served as the best model for the simulation of Hardness, Turb, and SS while the NARX model demonstrated high capability in predicting pH. Yet, the HW and NARX as system identification techniques attained best overall predictive performance among the four modeling approaches. The HW model offers, therefore, a reliable and intelligent approach for predicting the treated Hardness, Turb, and SS and should be explored as a predictive tool in TWTP. Among the non-linear ensemble models, GRNN-E proved of high merit and increased the accuracy of the best single models significantly up to 30% for Hardness and Turb, 34% for pH, and 37% for SS with regards to the single models.

Recent advances in the micro-electronics industry have increased the demand for smaller and more compact package devices with higher performance. This paper presents an analytical multiparametric design optimization approach for the miniaturization of flip-chip package, while considering the filling time of the subsequent underfill encapsulation process. The design optimization approach was based on the latest regional segregation-based analytical filling time model. Numerical simulation was conducted to verify the governed analytical model. The discrepancies in the filling times are less than 9.9%, and the predicted critical bump pitch has a low deviation of 4.1%, affirming that both the analytical and numerical models were in great consensus. The variation effects of bump pitch, gap height, and contact angle on the filling time were analyzed and discussed thoroughly. Both the critical bump pitch and the critical gap height were computed and fitted into respective empirical equations. Subsequently, a new multiparametric design optimization approach based on the thresholding and criticality of underfill parameters was proposed to determine the optimum parameters that yield to the most compact flip-chip package with acceptable low filling time during the encapsulation process. Lastly, this proposed optimization technique was tested on the four flip-chips used in a previously published underfill experiment.

Στην παρούσα διδακτορική διατριβή, μια σειρά από υλικά αξιολογήθηκαν ως προς την δυνατότητά τους να χρησιμοποιηθούν για την ανάπτυξη ηλεκτρονικών διατάξεων με την τεχνολογία εκτύπωσης inkjet. Δυο μελάνια βασισμένα σε νανοσωματίδια αργύρου με διαφορετικές τεχνικές σύντηξης (θερμικά και χημικά), ένα αγώγιμο πολυμερές (poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)), μια γραφενική διασπορά σταθεροποιημένη με αιθυλοκυτταρίνη σε κυκλοεξανόνη – terpineol και μια υδατική διασπορά μειωμένου οξειδίου του γραφενίου (f-rGO), χρησιμοποιήθηκαν για την ανάπτυξη αισθητήρων υγρασίας, θερμοκρασίας και μηχανικής κάμψης σε υποστρώματα χαρτιού και πολυιμιδίου. Επίσης, αξιολογήθηκαν τεχνικές ηλεκτρικής και μηχανικής διασύνδεσης δομών χαλκού σε πολυιμίδιο, οι οποίες συνενώθηκαν ηλεκτρικά και μηχανικά με εκτυπωμένες διατάξεις γραφενίου και νανοσωματιδίων αργύρου μέσω εμπορικών διασυνδέσεων, καθώς και μέσω απευθείας επιτύπωσης. Πραγματοποιήθηκε ενδελεχής βιβλιογραφική έρευνα με σκοπό την ανάδειξη συνδυασμών εκτυπώσιμων υλικών – υποστρωμάτων, κατάλληλων να υποστηρίξουν την μαζική, οικονομική κι επαναλήψιμη ανάπτυξη αισθητήρων μέσω inkjet. Δυο αισθητήρες υγρασίας με μετρούμενη έξοδο την ηλεκτρική αντίσταση αναπτύχθηκαν σε υπόστρωμα χαρτιού· ο πρώτος ήταν βασισμένος σε ηλεκτρόδια νανοσωματιδίων αργύρου ενώ ο δεύτερος σε PEDOT:PSS. Με την εφαρμογή αυτή, επιδείχθηκε η δυνατότητα χρήσης του υποστρώματος χαρτιού σαν ενεργό υλικό για μέτρηση σχετικής υγρασίας. Οι συσκευές παρουσίασαν μεταβολή στην τιμή της αντίστασης κατά μια τάξη μεγέθους ανά 10 %rH στο εύρος τιμών 0 ως 30 %rH και μεταβολή μιας τάξης μεγέθους στην αντίσταση ανά 20 %rH στο εύρος 30 – 90 %rH. Αισθητήρες θερμοκρασίας βασισμένοι σε νανοσωματίδια αργύρου και PEDOT:PSS σε χαρτί, και γραφένιο και f-rGO σε υπόστρωμα πολυιμιδίου αναπτύχθηκαν κι αξιολογήθηκαν σχετικά με τα ηλεκτρικά τους χαρακτηριστικά και τον θερμικό συντελεστή αντίστασής τους (TCR). Οι συντελεστές εξήχθησαν ως 9.389×10-4 oC-1, -0.0139 oC-1, -1.94x10-3 oC-1 και -1.64x10-2 oC-1 αντίστοιχα. Οι αισθητήρες βασισμένοι σε γραφενικά υλικά εμφάνισαν αντοχή στη θερμική καταπόνηση και μέσους χρόνους απόκρισης 2.47 s (γραφένιο) και 2.94 s (f-rGO). Επίσης, μελετήθηκαν αισθητήρες μηχανικής κάμψης από νανοσωματίδια αργύρου και PEDOT:PSS σε υπόστρωμα χαρτιού, με στόχο την ανάπτυξη μιας ολοκληρωμένης πλατφόρμας αισθητήρων, σε συνδυασμό με τους προαναφερθέντες αισθητήρες. Οι συντελεστές gauge (Gauge Factor) των συσκευών αυτών εξήχθησαν ως GFAgTensile = 0.4259 και GFPEDOT:PSSTensile = 0.1422 για παραμόρφωση μέσω εφελκυσμού. Για συμπιεστική παραμόρφωση οι παραπάνω συντελεστές διαμορφώθηκαν ως GFAgCompress = -0.1572 και PEDOT:PSS GFPEDOT:PSSCompress = 0.1448. Επίσης, πειράματα επαναλαμβανόμενης μηχανικής κάμψης 1000 κύκλων πραγματοποιήθηκαν χρησιμοποιώντας ένα XY stage ακριβείας. Τα αισθητήρια βασισμένα σε νανοσωματίδια αργύρου εμφάνισαν υψηλότερη μηχανική αντοχή. Μελετήθηκαν επίσης θερμικοί αισθητήρες ροής σε δυο διαστάσεις μέσω δυο προσεγγίσεων κατασκευής. Αρχικά χρησιμοποιώντας εμπορικά στοιχεία SMT πλατίνας σε επιχαλκωμένο υπόστρωμα πολυιμιδίου ως αισθητήρες και μικροθερμαντήρες με σκοπό την ανίχνευση του διανύσματος της ροής (πλάτος και γωνία). Για το πλάτος της ροής, δυο διαφορετικοί τρόποι λειτουργίας του μικροθερμαντήρα αξιολογήθηκαν, αυτός του σταθερού ρεύματος κι αυτός της σταθερής θερμοκρασίας. Ακολούθησε μεταφορά της τεχνολογίας σε μια πλήρως εκτυπωμένη διάταξη, με στοιχεία ενεργού άνθρακα – τιτανικού βαρίου (BaTiO3) σε υπόστρωμα PET. Αντίστοιχα, οι συσκευές αυτές μετρήθηκαν ως προς την ικανότητά τους να ανιχνεύσουν ροές αέρα σε δυο διαστάσεις. Επίσης, μελετήθηκε η υποβοήθηση λήψης αποφάσεως σχετικά με την κατεύθυνση της ροής μέσω νευρωνικού δικτύου εκπαιδευμένου με διαφορετικά σύνολα μετρήσεων. Οι δυο διατάξεις ήταν ικανές να μετρήσουν ροές στο εύρος 0 ως 25 SLPM, ενώ η μέθοδος λειτουργίας σταθερής θερμοκρασίας ήταν εμφανώς πιο ευαίσθητη στην ανίχνευση του πλάτους ροής (12.6 mW/(m/s) σε σχέση με -2.80 mW/(m/s) στον τρόπο λειτουργίας σταθερού ρεύματος). Εκτιμήθηκαν τέλος διαφορετικοί τρόποι ηλεκτρικής διασύνδεσης εκτυπωμένων μέσω inkjet δομών και παραδοσιακών δομών χαλκού σε εύκαμπτο υπόστρωμα πολυμιδίου. Ανάλογα με την εφαρμογή, κρίθηκαν αξιοποιήσιμες δυο εμπορικές λύσεις (Amphenol FPC & Clincher). Επίσης, η επιτύπωση δομών χαλκού με αγώγιμα υλικά φάνηκε να λειτουργεί αξιόπιστα, όμως σύμφωνα με μετρήσεις και προσομοίωση με μέθοδο πεπερασμένων στοιχείων, η τοποθέτηση των ηλεκτρικών επαφών παίζει σημαντικό ρόλο στη διαμόρφωση του ηλεκτρικού πεδίου και της πυκνότητας ρεύματος.

A method for calculating amplitudes and constructing frequency characteristics of forced and self-excited vibrations of a rotor-fluid-foundation system on rolling bearings with a non-linear characteristic based on the method of complex amplitudes and harmonic balance has been developed. Non-linear equations of motion of the rotor-fluid-foundation system are derived, and analytical methods of their solution are presented. Frequencies of fundamental and ultra-harmonic resonances are determined. The intervals between self-oscillation frequencies are estimated. The dependence of amplitudes on the amount of fluid in the rotor cavity, the mass of the foundation, linear imbalance, the value of the stiffness coefficient, and the damping coefficient is shown.

T1 and T2 relaxation times combined with 31 P spectroscopy have been proven efficient for muscular disease characterization as well as for pre- and post-muscle stimulation measurements. Even though 31 P spectroscopy can already be performed during muscle exercise, no method for T1 and T2 measurement enables this possibility. In this project, a complete setup and protocol for multi-parametrical MRI of the rat gastrocnemius before, during and after muscle stimulation at 4.7 and 7 T is presented. The setup is fully MRI compatible and is composed of a cradle, an electro-stimulator and an electronic card in order to synchronize MRI sequences with muscle stimulation. A 2D triggered radial-encoded Look-Locker sequence was developed, and enabled T1 measurements in less than 2 min on stimulated muscle. Also, a multi-slice multi-echo sequence was adapted and synchronized for T2 measurements as well as 31 P spectroscopy acquisitions in less than 4 min in both cases on stimulated muscle. Methods were validated on young rats using different stimulation paradigms. Then they were applied on older rats to compare quantification results, using the different stimulation paradigms, and allowed observation of metabolic changes related to aging with good reproducibility. The robustness of the whole setup shows wide application opportunities.

INTRODUCTION AND OBJECTIVE:Multi parametric MRI (mpMRI) has emerged as the most common tool to evaluate the need for biopsy in men referred for suspicion of prostate cancer, however PIRADS 3 remain...

INTRODUCTION AND OBJECTIVE:European and American urological guidelines of 2020 recommend to perform multiparametric (mp) MRI in men with suspicion of prostate cancer (PCa), before the execution of ...

BACKGROUND: Radiologists currently subjectively examine multi-parametric magnetic resonance imaging (MRI) to detect possible clinically significant lesions using the Prostate Imaging Reporting and Data System (PI-RADS) protocol. The assessment of imaging, however, relies on the experience and judgement of radiologists creating opportunity for inter-reader variability. Quantitative metrics, such as z-score and signal to clutter ratio (SCR), are therefore needed. METHODS: Multi-parametric MRI (T1, T2, diffusion, dynamic contrast-enhanced images) were resampled, rescaled, translated, and stitched to form spatially registered multi-parametric cubes for patients undergoing radical prostatectomy. Multi-parametric signatures that characterize prostate tumors were inserted into z-score and SCR. The multispectral covariance matrix was computed for the outlined normal prostate. The z-score from each MRI image was computed and summed. To reduce noise in the covariance matrix, following matrix decomposition, the noisy eigenvectors were removed. Also, regularization and modified regularization was applied to the covariance matrix by minimizing the discrimination score. The filtered and regularized covariance matrices were inserted into the SCR calculation. The z-score and SCR were quantitatively compared to Gleason scores from clinical pathology assessment of the histology of sectioned wholemount prostates. RESULTS: Twenty-six consecutive patients were enrolled in this retrospective study. Median patient age was 60 years (range, 49 to 75 years), median prostate-specific antigen (PSA) was 5.8 ng/mL (range, 2.3 to 23.7 ng/mL), and median Gleason score was 7 (range, 6 to 9). A linear fit of the summed z-score against Gleason score found a correlation of R=0.48 and a P value of 0.015. A linear fit of the SCR from regularizing covariance matrix against Gleason score found a correlation of R=0.39 and a P value of 0.058. The SCR employing the modified regularizing covariance matrix against Gleason score found a correlation of R=0.52 and a P value of 0.007. A linear fit of the SCR from filtering out 3 and 4 eigenvectors from the covariance matrix against Gleason score found correlations of R=0.50 and 0.44, respectively, and P values of 0.011 and 0.027, respectively. CONCLUSIONS: Z-score and SCR using filtered and regularized covariance matrices derived from spatially registered multi-parametric MRI correlates with Gleason score with highly significant P values.