Vintherdogan3397

Furthermore, the G20 porous structures (20% of porosity) exhibit microwave absorption coefficients ranging from 0.70 to 0.91 in the 12-18 GHz region and close to 1 at THz frequencies (300 GHz-1 THz). Results show that the simultaneous presence of MWCNTs and GE brings a significant enhancement of specific functional properties of the porous structures, which are proposed as potential actuators with relevant electro-magnetic interference (EMI) shielding properties.The paper presents the results of laboratory tests on possibilities to utilize active carbons produced in Poland (AG-5 and DTO) and clinoptilolite for removing naphthalene from a water solution in the adsorption process. The concentration of naphthalene in the model solution was 20 mg/dm3. The effects of pH, dose and adsorption time were determined under static conditions. Adsorption kinetics were consistent with the pseudo-second-order model (PSO). Among the applied models, the best fit was obtained using the Langmuir isotherms. The maximum adsorption capacity for the activated carbons (AG-5 and DTO) equaled 24.57 and 30.28 mg/g, respectively. For clinoptilolite, all the analyzed models of adsorption poorly described the adsorption process. ABT199 The flow conditions were realized by filtration method. On the basis of the obtained results, the breakthrough curves, so-called isoplanes, were prepared and served in turn to determine the adsorption capacities in flow conditions. The total adsorption capacities determined under dynamic conditions of the AG-5 and DTO activated carbons were 85.63 and 94.54 mg/g, respectively, and only 2.72 mg/g for clinoptilolite. The exit curves (isoplanes) were also utilized to determine the mass penetration zone (the adsorption front height), as well as to calculate the rate of mass-exchange zone advance.Scandium aluminum nitride (ScxAl1-xN) films are currently intensively studied for surface acoustic waves (SAW) filters and sensors applications, because of the excellent tradeoff they present between high SAW velocity, large piezoelectric properties and wide bandgap for the intermediate compositions with an Sc content between 10 and 20%. In this paper, the growth of Sc0.09Al0.91N and Sc0.18Al0.82N films on sapphire substrates by sputtering method is investigated. The plasma parameters were optimized, according to the film composition, in order to obtain highly-oriented films. X-ray diffraction rocking-curve measurements show a full width at half maximum below 1.5°. Moreover, high-resolution transmission electron microscopy investigations reveal the epitaxial nature of the growth. Electrical characterizations of the Sc0.09Al0.91N/sapphire-based SAW devices show three identified modes. Numerical investigations demonstrate that the intermediate compositions between 10 and 20% of scandium allow for the achievement of SAW devices with an electromechanical coupling coefficient up to 2%, provided the film is combined with electrodes constituted by a metal with a high density.There are twenty recurrent mutations in six breast-cancer-predisposing genes in Poland (BRCA1, BRCA2, CHEK2, PALB2, NBN, and RECQL). The frequencies of the twenty alleles have not been measured in a large series of early-onset breast cancer patients from Poland unselected for family history. We genotyped 2464 women with breast cancer diagnosed below age 41 years for twenty recurrent germline mutations in six genes, including BRCA1, BRCA2 CHEK2, PALB2, NBN, and RECQL. A mutation in one of the six genes was identified in 419 of the 2464 early-onset breast cancer cases (17%), including 22.4% of those cases diagnosed below age 31. The mutation frequency was 18.8% for familial breast cancer cases and 6% for non-familial cases. Among women with breast cancer below age 31, the mutation frequency was 23.6% for familial cases and 17.4% in non-familial cases. The majority of mutations (76.2%) were seen in BRCA1 and BRCA2. In Poland, a panel of twenty recurrent mutations in six genes can identify a genetic basis for a high percentage of early-onset cases and testing is recommended for all women with breast cancer at age 40 or below.

Biomarkers for predicting response to immune checkpoint inhibitors (ICI) are scarce and often lack external validation. This study provides a comprehensive investigation of pretreatment C-reactive protein (CRP) levels as well as its longitudinal trajectories as a marker of treatment response and disease outcome in patients with advanced non-small cell lung cancer (NSCLC) undergoing immunotherapy with anti PD-1 or anti PD-L1 agents.

We performed a retrospective bi-center study to assess the association between baseline CRP levels and anti PD-(L)1 treatment outcomes in the discovery cohort (

= 90), confirm these findings in an external validation cohort (

= 101) and explore the longitudinal evolution of CRP during anti PD-(L)1 treatment and the potential impact of dynamic CRP changes on treatment response and disease outcome in the discovery cohort. Joint models were implemented to evaluate the association of longitudinal CRP trajectories and progression risk. Primary treatment outcomes were progressionduction in PFS risk (HR = 0.91, 95% CI 0.83-0.99,

= 0.036), respectively.

These findings support the concept that CRP should be further explored by future prospective studies as a simple non-invasive biomarker for assessing treatment benefit during anti PD-(L)1 treatment in advanced NSCLC.

These findings support the concept that CRP should be further explored by future prospective studies as a simple non-invasive biomarker for assessing treatment benefit during anti PD-(L)1 treatment in advanced NSCLC.Internet of Things (IoT) projects are increasing in size over time, and some of them are growing to reach the whole world. Sensor arrays are deployed world-wide and their data is sent to the cloud, making use of the Internet. These huge networks can be used to improve the quality of life of the humanity by continuously monitoring many useful indicators, like the health of the users, the air quality or the population movements. Nevertheless, in this scalable context, a percentage of the sensor data readings can fail due to several reasons like sensor reliabilities, network quality of service or extreme weather conditions, among others. Moreover, sensors are not homogeneously replaced and readings from some areas can be more precise than others. In order to address this problem, in this paper we propose to use collaborative filtering techniques to predict missing readings, by making use of the whole set of collected data from the IoT network. State of the art recommender systems methods have been chosen to accomplish this task, and two real sensor array datasets and a synthetic dataset have been used to test this idea.