Miracle-dz/UniFAR-FTUs huggingface dataset:
A Patch Based Denoising Method Using Deep Convolutional Neural Network for Seismic Image

The deep convolutional neural networks (CNNs) have been shown excellent performances for image denoising. However, the denoising CNN model trained with a specific noise level cannot deal with the images which have spatiotemporally variant random noise and low signal-to-noise ratio (SNR), such as seismic images. To this end, we propose a patch-based denoising CNN method, namely PDCNN. Specifically, we cluster the overlapping patches of noisy image into $K $ classes where the image patches have close noise levels in each class, and then choose a suitable model for denoising the corresponding class from a series of well-trained CNN models. By embodying the structural statistics, we propose a CNN model selection criterion with a structural-dependent parameter. In contrast to the manual model selection process, the more accurate CNN model is chosen automatically and effectively. The capability of the PDCNN is demonstrated on synthetic and field seismic images. Experimental results show that the proposed method largely benefits from using multiple CNN models to jointly denoise, and leads to the satisfactory denoising performance in spatiotemporally variant seismic random noise reduction and structural signal preservation.
Core supporters and long-term party switchers in U.S. Presidential Elections

We analyze long term voter migration induced by an ideological realignment of Democratic and Republican elites on economic, moral and other issues. When party positions change to create sharper contrasts on social issues, and/or less sharp differences on economic issues, then voters with socially-conservative, but economically-liberal preferences are likely to switch their support from Democrats to Republicans, and vice versa. Using data from the National Election Survey, we analyze the demographic characteristics, intelligence, ideological preferences and media consumption of these two groups of “switch voters. ” We also compare them with the two parties’ core supporters, and analyze the central ideological conflicts between and within each party’s coalition of supporters.
Screening for post‐traumatic stress disorders in 1017 cancer patients and correlation with anxiety, depression, and distress

Post‐traumatic stress disorder (PTSD) is a severe psychiatric disorder, which might develop after a traumatic event, like cancer diagnosis, and threatens the patient's psychological and/or physiological integrity. Anxiety, depression, and mental distress are known to be common in cancer patients; however, the frequency of PTSD was not investigated thoroughly in this patient group so far. Here, we aim to screen cancer patients for PTSD symptoms and determine a possible correlation with anxiety, depression, and distress.
Target counting with Presburger constraints and its application in sensor networks

One of the applications popularized by the emergence of wireless sensor networks is target counting: the computational task of determining the total number of targets located in an area by aggregating the individual counts of each sensor. The complexity of this task lies in the fact that sensing ranges may overlap, and therefore, targets may be overcounted as, in this setting, they are assumed to be indistinguishable from each other. In the literature, this problem has been proven to be unsolvable, hence the existence of several estimation algorithms. However, the main limitation currently affecting these algorithms is that no assurance regarding the precision of a solution can be given. We present a novel algorithm for target counting based on exhaustive enumeration of target distributions using linear Presburger constraints. We improve on current approaches since the estimated counts obtained by our algorithm are by construction guaranteed to be consistent with the counts of each sensor. We further extend our algorithm to allow for weighted topologies and sensing errors for applicability in real-world deployments. We evaluate our approach through an extensive collection of synthetic and real-life configurations.
Impact of Blood Metabolite Profile and Milk Yield on Fertility of Dairy Cows

Received: Revised: Accepted: 2014–10–17 2014–10–28 2014–10–29 This study was conducted to evaluate the influence of blood metabolites (glucose and urea) and milk yield on fertility of local non–descript dairy cows. For this purpose, blood samples were collected from one hundred cows on day 1 (pre–insemination) and day 21 (post insemination). Data pertaining to age, body condition score, milk yield and fertility attributes of selected animals were recoded using a structured questionnaire. Contrary to non–pregnant cows, the pregnant animals demonstrated relatively lower blood glucose levels. Glucose concentration in the blood was directly proportional to body condition score. Blood urea concentration varied significantly between conceived and non–conceived groups. Non– pregnant group exhibited comparatively lower blood urea levels as compared to pregnant group. Different age groups displayed a non–significant disparity in terms of blood metabolites concentration. Difference in milk yield between the pregnant and non pregnant cows was statistically non–significant. This study validated that blood glucose, blood urea and milk yield could not be regarded as specific determinants of fertility in non–descript dairy cows. All copyrights reserved to Nexus® academic publishers
Oxylipins Other Than Jasmonic Acid Are Xylem-Resident Signals Regulating Systemic Resistance Induced by Trichoderma virens in Maize

The long-distance signals 12-OPDA and KODA activate induced systemic resistance (ISR) triggered by the root-colonizing beneficial fungal endophyte Trichoderma virens. Multiple long-distance signals have been identified for pathogen-induced systemic acquired resistance, but mobile signals for symbiont-induced systemic resistance (ISR) are less well understood. We used ISR-positive and -negative mutants of maize (Zea mays) and the beneficial fungus Trichoderma virens and identified 12-oxo-phytodienoic acid (12-OPDA) and α-ketol of octadecadienoic acid (KODA) as important ISR signals. We show that a maize 13-lipoxygenase mutant, lox10, colonized by the wild-type T. virens (TvWT) lacked ISR response against Colletotrichum graminicola but instead displayed induced systemic susceptibility. Oxylipin profiling of xylem sap from T. virens–treated plants revealed that 12-OPDA and KODA levels correlated with ISR. Transfusing sap supplemented with 12-OPDA or KODA increased receiver plant resistance in a dose-dependent manner, with 12-OPDA restoring ISR of lox10 plants treated with TvWT or T. virens Δsm1, a mutant unable to induce ISR. Unexpectedly, jasmonic acid (JA) was not involved, as the JA-deficient opr7 opr8 mutant plants retained the capacity for T. virens–induced ISR. Transcriptome analysis of TvWT-treated maize B73 revealed upregulation of 12-OPDA biosynthesis and OPDA-responsive genes but downregulation of JA biosynthesis and JA response genes. We propose a model that differential regulation of 12-OPDA and JA in response to T. virens colonization results in ISR induction.
Validation and Adaptation of the Multidimensional Prognostic Index in an Older Australian Cohort

Background and aims: The Multidimensional Prognostic Index (MPI), an objective and quantifiable tool based on the Comprehensive Geriatric Assessment, has been shown to predict adverse outcomes in European cohorts. We conducted a validation study of the original MPI, and of adapted versions that accounted for the use of specific drugs and cultural diversity in the assessment of cognition, in older Australians. Methods: The capacity of the MPI to predict 12-month mortality was assessed in 697 patients (median age: 80 years; interquartile range: 72–86) admitted to a metropolitan teaching hospital between September 2015 and February 2017. Results: In simple logistic regression analysis, the MPI was associated with 12-month mortality (Low risk: OR reference group; moderate risk: OR 2.50, 95% CI: 1.67–3.75; high risk: OR 4.24, 95% CI: 2.28–7.88). The area under the receiver operating characteristic curve (AUC) for the unadjusted MPI was 0.61 (0.57–0.65) and 0.64 (95% CI: 0.59–0.68) with age and sex adjusted. The adapted versions of the MPI did not significantly change the AUC of the original MPI. Conclusion: The original and adapted MPI were strongly associated with 12-month mortality in an Australian cohort. However, the discriminatory performance was lower than that reported in European studies.
The bactericidal effect of an atmospheric-pressure plasma jet on Porphyromonas gingivalis biofilms on sandblasted and acid-etched titanium discs

Purpose Direct application of atmospheric-pressure plasma jets (APPJs) has been established as an effective method of microbial decontamination. This study aimed to investigate the bactericidal effect of direct application of an APPJ using helium gas (He-APPJ) on Porphyromonas gingivalis biofilms on sandblasted and acid-etched (SLA) titanium discs. Methods On the SLA discs covered by P. gingivalis biofilms, an APPJ with helium (He) as a discharge gas was applied at 3 different time intervals (0, 3, and 5 minutes). To evaluate the effect of the plasma itself, the He gas–only group was used as the control group. The bactericidal effect of the He-APPJ was determined by the number of colony-forming units. Bacterial viability was observed by confocal laser scanning microscopy (CLSM), and bacterial morphology was examined by scanning electron microscopy (SEM). Results As the plasma treatment time increased, the amount of P. gingivalis decreased, and the difference was statistically significant. In the SEM images, compared to the control group, the bacterial biofilm structure on SLA discs treated by the He-APPJ for more than 3 minutes was destroyed. In addition, the CLSM images showed consistent results. Even in sites distant from the area of direct He-APPJ exposure, decontamination effects were observed in both SEM and CLSM images. Conclusions He-APPJ application was effective in removing P. gingivalis biofilm on SLA titanium discs in an in vitro experiment.
Pocket-like active site of Rh1/MoS2 single-atom catalyst for selective crotonaldehyde hydrogenation.

Selective hydrogenation of unsaturated aldehydes to unsaturated alcohols is a valuable but challenging task for synthesizing fine chemicals. We report that single Rh atoms anchored to the edges of 2D MoS2 sheets can efficiently convert crotonalde-hyde to crotyl alcohol with 100% selectivity via a steric confinement effect of pocket-like active sites. Characterization results suggest that the synthesized Rh1/MoS2 single-atom catalysts (SACs) possess a unique geometric and electronic configuration, which confines the adsorption mode of the reactant molecule by a steric effect. The DFT calculations suggest that the MoS2 sheets terminate with oxidized Mo edges and the Rh1 stably anchors at the Mo cati-on vacancy site, which can facilely dissociate H2 to H atoms. The dissociated H atoms spillover to react with the edge O atoms to form OH species and create an HO-Mo-Rh1-Mo-OH configuration, resembling a pocket-like active site, which confines the adsorption mode of the crotonaldehyde due to steric effects. Such specific adsorption configuration yields 100% selectivity. The strategy of constructing pocket-like active centers with single metal atoms and 2D nanosheets opens new approaches to designing high-ly selective SACs for specific classes of catalytic transformations.
Joha Rice: An aromatic indigenous rice of Assam, India contains flavanoids and phenolic substances and shows good antioxidant activities

The objective of present work is to study the in-vitro anti-oxidant activities of Joha Rice; an aromatic indigenous rice of Assam, India. Anti-oxidant activity of the extracts were studied using 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity, Hyderogen peroxide(H2O2) scavenging activity and Nitric Oxide(NO) scavenging activity. The total Phenolic contents and Flavanoid contents were estimated taking Gallic Acid and Quercetin calibration curve respectably. In in-vitro anti-oxidant studies it was found that ethanolic extract of Joha Rice posses good free radical scavenging activity and was comparable with standard Ascorbic acid. The IC 50 for Joha Rice was found in DPPH scavenging activity 81.45±2.29 μg/ml, Hydrogen Peroxide scavenging activity 121.30±2.20 μg/ml and Nitric Oxide scavenging activity 137.67±3.34. The total Phenolic content was found 74.86±2.474 mg/gm Eq of Gallic Acid and Total Flavanoid content was 190.7±15.28 mg/gm Eq of Quercetin. Ethanolic extract of Joha Rice contains phenolic and Flavanoids and posses anti-oxidant activities in In-vitro methods. So, we can further use this for screening of biological activities in metabolic and degenerative diseases which were cause due to free radical mechanism.
The most metal-poor Galactic globular cluster: the first spectroscopic observations of ESO280-SC06

We present the first spectroscopic observations of the very metal-poor Milky Way globular cluster ESO280-SC06. Using spectra acquired with the 2dF/AAOmega spectrograph on the Anglo-Australian Telescope, we have identified 13 members of the cluster, and estimate from their infrared calcium triplet lines that the cluster has a metallicity of $\mathrm{[Fe/H]}=-2.48\substack{+0.06 \\ -0.11}$. This would make it the most metal-poor globular cluster known in the Milky Way. This result was verified with comparisons to three other metal-poor globular clusters that had been observed and analyzed in the same manner. We also present new photometry of the cluster from EFOSC2 and SkyMapper and confirm that the cluster is located $22.9\pm2.1$ kpc from the Sun and $15.2\pm2.1$ kpc from the Galactic centre, and has a radial velocity of $92.5\substack{+2.4 \\ -1.6}$ km s$^{-1}$. These new data finds the cluster to have a radius about half that previously estimated, and we find that the cluster has a dynamical mass of the cluster of $(12\pm2)\times10^3$ solar masses. Unfortunately, we lack reliable proper motions to fully characterize its orbit about the Galaxy. Intriguingly, the photometry suggests that the cluster lacks a well-populated horizontal branch, something that has not been observed in a cluster so ancient or metal-poor.
Application of Monochromatic Imaging and Metal Artifact Reduction Software in Computed Tomography Angiography after Treatment of Cerebral Aneurysms.

PURPOSE This study aimed to evaluate the image quality and degree of metal artifact reduction using the new-generation gemstone spectral imaging (GSI) and metal artifact reduction software (MARs) and to demonstrate the optimal monochromatic energy level for dual-energy cerebral computed tomography angiography (CTA) in patients with intracranial aneurysm after endovascular treatment. MATERIAL AND METHODS A total of 20 patients with cerebral aneurysms treated with coils or clips underwent CTA using gemstone spectral computed tomography. Artifact index was calculated at each energy level with and without MARs. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated on all axial images with MARs; subjective evaluation was done by using a 4-point scale and a 3-point scale for assessing noise and vessel contrast, respectively, and compared between the monochromatic energy levels. RESULTS The artifact index value of group GSI-MARs was significantly lower than that of group GSI at each monochromatic energy level (all, P < 0.01). Contrast-to-noise ratio and SNR of the parent arteries decreased as the energy increased from 40 to 140 keV in group GSI-MARs (all, P < 0.01). Signal-to-noise ratio and CNR between each 2 adjacent monochromatic energy level showed significant difference (all, P < 0.01). Subjective evaluation showed that a monochromatic energy level between 40 and 70 keV provided the optimal image quality. CONCLUSION Gemstone spectral imaging with MARs could reduce metal artifacts and improve the image quality of cerebral CTA after coil or clip treatment. The new generation of GSI could provide better CNR and SNR at lower energy level, and the best image quality was obtained at energy level 40 to 70 keV for GSI-MARs.
Effectively persuading prospects to adopt a high value product that originates from Poland

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
Predictive value of ischaemia‐modified albumin in spermatogenesis in an experimental testicular torsion model

Our aim was to measure the ability of ischaemia‐modified albumin (IMA) to predict testicular histopathological damage in the testes of rats with short‐ and long‐term ischaemia using experimental testicular torsion and subsequent reperfusion via detorsion.21 Wistar Albino rats were randomized into three groups. The sham group was subjected to a mid‐scrotal incision only. The 4‐ and 8‐hr T/D (Torsion/Detorsion) groups were subjected to left testicular torsion by twisting the testes by 720 degrees counterclockwise. 2 cc venous blood samples were taken from the sham group after the mid‐scrotal incision, and from the 4‐ and 8‐hr T/D groups after 4 and 8 hr respectively. After that, the 4‐ and 8‐hr T/D groups were subjected to detorsion. Two days later, orchiectomy was performed. Ischaemia‐modified albumin levels were significantly different among the groups at 48 hr prior to orchiectomy (reperfusion; p = .003). Based on the results of the paired comparisons, it was found that IMA levels of the sham group were significantly higher than those of the 4‐ and 8‐hr T/D groups (p = .002 and .009 respectively). Our study has showed that IMA may be used to predict ischaemia/reperfusion injury, which is another complication that may occur following detorsion in testicular torsion.
The impact of incorrectly selected soil permittivity value on focused GPR image

This article presents simulation and measurement results of ground penetrating radar with FMCW (Frequency Modulated Continuous Wave) signal. The author shows the effect of incorrectly chosen permittivity value of tested soil on final SAR (Synthetic Aperture Radar) image. Novel iterative AutoESP (Auto Estimation of Soil Permittivity) algorithm is tested on actual measurement GPR data. Streszczenie. Artykul przedstawia wyniki symulacji oraz rzeczywistych pomiarow radarem do sondowan podpowierzchniowych GPR z modulacją FMCW (ang. Frequency Modulated Continuous Wave). Autor prezentuje wplyw blednie dobranej przenikalności elektrycznej badanej ziemi na koncowe zobrazowanie SAR (ang. Synthetic Aperture Radar). W artykule zamieszczono wyniki testowan nowego, iteracyjnego algorytmu AutoESP (ang. Auto Estimation of Soil Permittivity). (Wplyw blednie dobranej wartości przenikalności elektrycznej ziemi na zogniskowane zobrazowanie GPR)
Measurement of electromigration parameters of lead-free SnAg3.5 solder using U-groove lines

Measurement of electromigration parameters in the lead-free solder SnAg3.5 was carried out by utilizing U-groove solder lines and atomic force microscopy in the temperature range of 100-150 °C. The drift velocity was measured, and the threshold current densities of the SnAg3.5 solder were estimated to be 4.4 × 10^4 A/cm^2 at 100 °C, 3.3 × 10^4 A/cm^2 at 125 °C, and 5.7 × 10^3 A/cm^2 at 150 °C. These values represent the maximum current densities that the SnAg3.5 solder can carry without electromigration damage at the three stressing temperatures. The critical products for the SnAg3.5 solder were estimated to be 462 A/cm at 100 °C, 346 A/cm at 125 °C, and 60 A/cm at 150 °C. In addition, the electromigration activation energy was determined to be 0.55 eV in the temperature range of 100-150 °C. These values are very fundamental for current carrying capability and mean-time-to-failure measurement for solder bumps. This technique enables the direct measurement of electromigration parameters of solder materials.
Analysis of the Wind Dependent Duration of the Cruise Phase on Jet Engine Exhaust Emissions

Abstract Nowadays more and more attention is paid to minimizing the costs of air operations. The largest share in the cost of the flight is the cost of consumed fuel. Taking into account the external conditions, having impact on the aircraft, such as wind direction and magnitude when planning the aircraft trajectory it is possible to reduce flight time and thus reduce fuel consumption. An additional advantage is the simultaneous reduction of pollutants in the jet engines exhausts. In the times of pro-ecological trends and concepts (e.g. Clean Sky, Single European Sky, CORSIA) this aspect is of crucial importance. The emission of selected pollutants in the jet engine exhausts (NOx, CO and HC) emitted during the flight of a business jet on the route whose cruise phase was assumed 1000 km long was determined in the article. The aircraft used in the research was Gulfstream GIV, powered by two Rolls Royce TAY 611-C engines, for which a cruising altitude of 10 km and a flight speed of 0.8 Ma were assumed. The thrust necessary for the flight at these cruise parameters was set, and then the engine thrust appropriate for the flight and the corresponding specific fuel consumption were determined. On this basis, based on the available ICAO data, the emission of selected pollutants in tis engines exhausts was determined for windless conditions. Next, the analysis of the impact of wind - its magnitude and direction – on the emission of these pollutants was made. The results of the conducted analyses are presented in diagrams and discussed in the conclusions.
The statistics of how natural images drive the responses of neurons

To model the responses of neurons in the early visual system, at least three basic components are required: a receptive field, a normalization term, and a specification of encoding noise. Here, we examine how the receptive field, the normalization factor, and the encoding noise affect the drive to model-neuron responses when stimulated with natural images. We show that when these components are modeled appropriately, the response drives elicited by natural stimuli are Gaussian-distributed and scale invariant, and very nearly maximize the sensitivity (d′) for natural-image discrimination. We discuss the statistical models of natural stimuli that can account for these response statistics, and we show how some commonly used modeling practices may distort these results. Finally, we show that normalization can equalize important properties of neural response across different stimulus types. Specifically, narrowband (stimulus- and feature-specific) normalization causes model neurons to yield Gaussian response-drive statistics when stimulated with natural stimuli, 1/f noise stimuli, and white-noise stimuli. The current work makes recommendations for best practices and lays a foundation, grounded in the response statistics to natural stimuli, upon which to build principled models of more complex visual tasks.