Silesian University of Technology

In the field of luminescence and electron spin resonance dating, dose rate conversion factors are widely used to convert concentrations of radioactive isotopes to dose rate values. These factors are derived from data provided by the National Nuclear Data Center of the Brookhaven National Laboratory, which are compiled in Evaluated Nuclear Structure Data Files (ENSDF) and Nuclear Wallet Cards. The recalculated dose rate conversion factors are a few percent higher than those previously published, except for beta and gamma emissions of the isotopes of the U-series decay chains.

This article reports or, the international Nanofluid Property Benchmark Exercise, or INPBE. in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles or "nanofluids", was measured by over 30 organizations worldwide, using, a variety of experimental approaches, including the transient hot wire method, steady-state methods, and optical methods. The nanofluids tested in the exercise were comprised of aqueous and nonaqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (+/- 10% or less) about the sample average with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio. as expected from classical theory. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however. such differences tend to disappear when the data are normalized to the Measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.

Standardised image databases or rather the lack of them are one of the main weaknesses in the field of content based image retrieval (CBIR). Authors often use their own images or do not specify the source of their datasets. Naturally this makes comparison of results somewhat difficult. While a first approach towards a common colour image set has been taken by the MPEG 7 committee their database does not cater for all strands of research in the CBIR community. In particular as the MPEG-7 images only exist in compressed form it does not allow for an objective evaluation of image retrieval algorithms that operate in the compressed domain or to judge the influence image compression has on the performance of CBIR algorithms. In this paper we introduce a new dataset, UCID (pronounced "use it") - an Uncompressed Colour Image Dataset which tries to bridge this gap. The UCID dataset currently consists of 1338 uncompressed images together with a ground truth of a series of query images with corresponding models that an ideal CBIR algorithm would retrieve. While its initial intention was to provide a dataset for the evaluation of compressed domain algorithms, the UCID database also represents a good benchmark set for the evaluation of any kind of CBIR method as well as an image set that can be used to evaluate image compression and colour quantisation algorithms.

The use of nanotechnology has the potential to revolutionize the detection and treatment of cancer. Developments in protein engineering and materials science have led to the emergence of new nanoscale targeting techniques, which offer renewed hope for cancer patients. While several nanocarriers for medicinal purposes have been approved for human trials, only a few have been authorized for clinical use in targeting cancer cells. In this review, we analyze some of the authorized formulations and discuss the challenges of translating findings from the lab to the clinic. This study highlights the various nanocarriers and compounds that can be used for selective tumor targeting and the inherent difficulties in cancer therapy. Nanotechnology provides a promising platform for improving cancer detection and treatment in the future, but further research is needed to overcome the current limitations in clinical translation.

Abstract This article focuses on ion transport through nanoporous systems with special emphasis on rectification phenomena. The effect of ion‐current rectification is observed as asymmetric current–voltage ( I–V ) curves, with the current recorded for one voltage polarity higher than the current recorded for the same absolute value of voltage of opposite polarity. This diode‐like I–V curve indicates that there is a preferential direction for ion flow. Experimental evidence that ion‐current rectification is inherent to asymmetric, e.g., tapered, nanoporous systems with excess surface charge is provided and discussed. The fabrication and operation of asymmetric polymer nanopores, gold nanotubes, glass nanocapillaries, and silicon nanopores are presented. The possibility of tuning the direction and extent of rectification is discussed in detail. Theoretical models that have been developed to explain the ion‐current rectification effect are also presented.

SUMMARY: Counting all k -mers in a given dataset is a standard procedure in many bioinformatics applications. We introduce KMC3, a significant improvement of the former KMC2 algorithm together with KMC tools for manipulating k -mer databases. Usefulness of the tools is shown on a few real problems. AVAILABILITY AND IMPLEMENTATION: Program is freely available at http://sun.aei.polsl.pl/REFRESH/kmc . CONTACT: sebastian.deorowicz@polsl.pl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pneumonia is among the top diseases which cause most of the deaths all over the world. Virus, bacteria and fungi can all cause pneumonia. However, it is difficult to judge the pneumonia just by looking at chest X-rays. The aim of this study is to simplify the pneumonia detection process for experts as well as for novices. We suggest a novel deep learning framework for the detection of pneumonia using the concept of transfer learning. In this approach, features from images are extracted using different neural network models pretrained on ImageNet, which then are fed into a classifier for prediction. We prepared five different models and analyzed their performance. Thereafter, we proposed an ensemble model that combines outputs from all pretrained models, which outperformed individual models, reaching the state-of-the-art performance in pneumonia recognition. Our ensemble model reached an accuracy of 96.4% with a recall of 99.62% on unseen data from the Guangzhou Women and Children’s Medical Center dataset.

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Nanoparticles (NPs) have become one of the most popular objects of scientific study during the past decades. However, despite wealth of study reports, still there is a gap, particularly in health toxicology studies, underlying mechanisms, and related evaluation models to deeply understanding the NPs risk effects. In this review, we first present a comprehensive landscape of the applications of NPs on health, especially addressing the role of NPs in medical diagnosis, therapy. Then, the toxicity of NPs on health systems is introduced. We describe in detail the effects of NPs on various systems, including respiratory, nervous, endocrine, immune, and reproductive systems, and the carcinogenicity of NPs. Furthermore, we unravels the underlying mechanisms of NPs including ROS accumulation, mitochondrial damage, inflammatory reaction, apoptosis, DNA damage, cell cycle, and epigenetic regulation. In addition, the classical study models such as cell lines and mice and the emerging models such as 3D organoids used for evaluating the toxicity or scientific study are both introduced. Overall, this review presents a critical summary and evaluation of the state of understanding of NPs, giving readers more better understanding of the NPs toxicology to remedy key gaps in knowledge and techniques.

The idea of exergy—a notion which nowadays is becoming increasingly widespread—was recently introduced into the field of radiation. In this paper formulas for the computation of exergy of heat radiation are set out. The ratio of exergy to the radiation energy has been considered and a discussion is presented of the dependence of substance exergy and radiation on temperature. In addition, the possible applications of radiation energy are mentioned as well as numerical examples using the relations derived in this paper.

We present a synthetic nanodevice, which transports potassium ions against their concentration gradient if stimulated with external field fluctuations. It consists of a single, conical pore, created in a thin polyethylene terephthalate film. The pumping mechanism is similar to one of longitudinally oscillating deterministic ratchets.

Here, a comprehensive photophysical investigation of a the emitter molecule DPTZ‐DBTO2 , showing thermally activated delayed fluorescence (TADF), with near‐orthogonal electron donor (D) and acceptor (A) units is reported. It is shown that DPTZ‐DBTO2 has minimal singlet–triplet energy splitting due to its near‐rigid molecular geometry. However, the electronic coupling between the local triplet ( 3 LE) and the charge transfer states, singlet and triplet, ( 1 CT, 3 CT), and the effect of dynamic rocking of the D–A units about the orthogonal geometry are crucial for efficient TADF to be achieved. In solvents with low polarity, the guest emissive singlet 1 CT state couples directly to the near‐degenerate 3 LE, efficiently harvesting the triplet states by a spin orbit coupling charge transfer mechanism (SOCT). However, in solvents with higher polarity the emissive CT state in DPTZ‐DBTO2 shifts below (the static) 3 LE, leading to decreased TADF efficiencies. The relatively large energy difference between the 1 CT and 3 LE states and the extremely low efficiency of the 1 CT to 3 CT hyperfine coupling is responsible for the reduction in TADF efficiency. Both the electronic coupling between 1 CT and 3 LE, and the (dynamic) orientation of the D–A units are thus critical elements that dictate reverse intersystem crossing processes and thus high efficiency in TADF.

PURPOSE: Ion channel activity is involved in several basic cellular behaviors that are integral to metastasis (e.g., proliferation, motility, secretion, and invasion), although their contribution to cancer progression has largely been ignored. The purpose of this study was to investigate voltage-gated Na(+) channel (VGSC) expression and its possible role in human breast cancer. EXPERIMENTAL DESIGN: Functional VGSC expression was investigated in human breast cancer cell lines by patch clamp recording. The contribution of VGSC activity to directional motility, endocytosis, and invasion was evaluated by in vitro assays. Subsequent identification of the VGSC alpha-subunit(s) expressed in vitro was achieved using reverse transcription-PCR, immunocytochemistry, and Western blot techniques and used to investigate VGSCalpha expression and its association with metastasis in vivo. RESULTS: VGSC expression was significantly up-regulated in metastatic human breast cancer cells and tissues, and VGSC activity potentiated cellular directional motility, endocytosis, and invasion. Reverse transcription-PCR revealed that Na(v)1.5, in its newly identified "neonatal" splice form, was specifically associated with strong metastatic potential in vitro and breast cancer progression in vivo. An antibody specific for this form confirmed up-regulation of neonatal Na(v)1.5 protein in breast cancer cells and tissues. Furthermore, a strong correlation was found between neonatal Na(v)1.5 expression and clinically assessed lymph node metastasis. CONCLUSIONS: Up-regulation of neonatal Na(v)1.5 occurs as an integral part of the metastatic process in human breast cancer and could serve both as a novel marker of the metastatic phenotype and a therapeutic target.

Depending on their structure and order (individual, films, bundled, buckypapers, etc.), carbon nanotubes (CNTs) demonstrate different values of thermal conductivity, from the level of thermal insulation with the thermal conductivity of 0.1 W/mK to such high values as 6600 W/mK. This review article concentrates on analyzing the articles on thermal conductivity of CNT networks. It describes various measurement methods, such as the 3-x method, bolometric, steady-state method and their variations, hot-disk method, laser flash analysis, thermoreflectance method and Raman spectroscopy, and summarizes the results obtained using those techniques. The article provides the main factors affecting the value of thermal conductivity, such as CNT density, number of defects in their structure, CNT ordering within arrays, direction of measurement in relation to their length, temperature of measurement and type of CNTs. The practical methods of using CNT networks and the potential directions of future research in that scope were also described.

The main sources of non-exhaust vehicular emissions that contribute to road dust are tire, brake and clutch wear, road surface wear, and other vehicle and road component degradation. This study is an attempt to identify and investigate heavy metals in urban and motorway road dusts as well as in dust from brake linings and tires. Road dust was collected from sections of the A-4 motorway in Poland, which is part of European route E40, and from urban roads in Katowice, Poland. Dust from a relatively unpolluted mountain road was collected and examined as a control sample. Selected metals Cd, Cr, Cu, Ni, Pb, Zn, Fe, Se, Sr, Ba, Ti, and Pd were analyzed using inductively coupled plasma-mass spectrometry, inductively coupled plasma (ICP)-optical emission spectroscopy, and atomic absorption spectroscopy on a range of size-fractionated road dust and brake lining dust (<20, 20-56, 56-90, 90-250, and >250 μm). The compositions of brake lining and tire dust were also investigated using scanning electron microscopy-energy-dispersive spectroscopy. To estimate the degree of potential environmental risk of non-exhaust emissions, comparison with the geochemical background and the calculations of geo-accumulation indices were performed. The finest fractions of urban and motorway dusts were significantly contaminated with all of the investigated metals, especially with Ti, Cu, and Cr, which are well-recognized key tracers of non-exhaust brake wear. Urban dust was, however, more contaminated than motorway dust. It was therefore concluded that brake lining and tire wear strongly contributed to the contamination of road dust.

]phenazine (DBPHZ) as an acceptor and phenothiazines (PTZ) as donors have been developed. Most importantly, the D-A-D compounds exhibit not only distinct tricolor-changeable mechanochromic luminescence (MCL) properties but also efficient thermally activated delayed fluorescence (TADF). Quantum chemical calculations, X-ray diffraction analysis, and systematic studies on the photophysical properties indicated that the "two-conformation-switchable" PTZ units play a highly important role in achieving multi-color-changing MCL. Time-resolved photophysical measurements revealed that the developed D-A-D compounds also exhibit efficient orange-TADF. Furthermore, organic light-emitting diode (OLED) devices fabricated with the new TADF emitters have achieved high external quantum efficiencies (EQEs) up to 16.8%, which significantly exceeds the theoretical maximum (∼5%) of conventional fluorescent emitters.

The environmental occurrence of antimicrobial pharmaceuticals and antibiotic resistant bacteria and antibiotic resistant genes has become a global phenomenon and a multifaceted threat. Integrated actions of many parties are needed to prevent further aggravation of the problem. Well-directed actions require clear understanding of the problem, which can be ensured by frequent revaluation of the existing knowledge and disseminating it among relevant audiences. The goal of this review paper is to discuss the occurrence and abundance of antimicrobial pharmaceuticals in the aquatic environment in context of adverse effects caused directly by these substances and the threat associated with the antibiotics resistance phenomenon. Several classes of antimicrobial pharmaceuticals (aminoglycosides, β-lactams, glycopeptides, macrolides, fluoroquinolones, sulfonamides and trimethoprim, tetracyclines) have been selected to illustrate their sources, environmental abundance, degradation routes (transformation products) and environmental implications including their ecotoxic effect and the spread of antibiotic resistance within the compartments of the aquatic environment and wastewater treatment plants. Wastewater treatment plants are indeed the main source responsible for the prevalence of these factors in the aquatic environment, since predominantly the plants have not been designed to retain antimicrobial pharmaceuticals. In order to limit the prevalence of these impurities into the environment, better source control is recommended as well as the establishment of stricter environmental quality standards. Counteracting all the above-mentioned threats requires to undertake integrated activities based on cooperation of professionals and scientists from various fields of science or industry, such as environmental sciences, medicine, veterinary, pharmacology, chemical engineering and others.

Manual identification of brain tumors is an error-prone and tedious process for radiologists; therefore, it is crucial to adopt an automated system. The binary classification process, such as malignant or benign is relatively trivial; whereas, the multimodal brain tumors classification (T1, T2, T1CE, and Flair) is a challenging task for radiologists. Here, we present an automated multimodal classification method using deep learning for brain tumor type classification. The proposed method consists of five core steps. In the first step, the linear contrast stretching is employed using edge-based histogram equalization and discrete cosine transform (DCT). In the second step, deep learning feature extraction is performed. By utilizing transfer learning, two pre-trained convolutional neural network (CNN) models, namely VGG16 and VGG19, were used for feature extraction. In the third step, a correntropy-based joint learning approach was implemented along with the extreme learning machine (ELM) for the selection of best features. In the fourth step, the partial least square (PLS)-based robust covariant features were fused in one matrix. The combined matrix was fed to ELM for final classification. The proposed method was validated on the BraTS datasets and an accuracy of 97.8%, 96.9%, 92.5% for BraTs2015, BraTs2017, and BraTs2018, respectively, was achieved.

ABSTRACT This paper presents a compilation of atmospheric radiocarbon for the period 1950–2019, derived from atmospheric CO 2 sampling and tree rings from clean-air sites. Following the approach taken by Hua et al. (2013), our revised and extended compilation consists of zonal, hemispheric and global radiocarbon ( 14 C) data sets, with monthly data sets for 5 zones (Northern Hemisphere zones 1, 2, and 3, and Southern Hemisphere zones 3 and 1–2). Our new compilation includes smooth curves for zonal data sets that are more suitable for dating applications than the previous approach based on simple averaging. Our new radiocarbon dataset is intended to help facilitate the use of atmospheric bomb 14 C in carbon cycle studies and to accommodate increasing demand for accurate dating of recent (post-1950) terrestrial samples.

In this paper, the influences of the graphite precursor and the oxidation method on the resulting reduced graphene oxide (especially its composition and morphology) are shown. Three types of graphite were used to prepare samples for analysis, and each of the precursors was oxidized by two different methods (all samples were reduced by the same method of thermal reduction). Each obtained graphite oxide and reduced graphene oxide was analysed by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy (RS).