Flotation collector O-isopropyl N-ethylthionocarbamate (IPETC) is widely used for separation of sulfide ores. Its removal from water by several oxidation processes was studied. Photocatalytic oxidation with air in the presence of iron salts, utilizing solar irradiation or artificial UV-A light is very efficient. Oxidation leads through the formation of O-isopropyl N-ethylcarbamate and several other reaction intermediates to total decomposition of organic compound in the final stage in 1 day. Similar results were obtained with a Fenton type oxidation with hydrogen peroxide and iron salts. Treatment with sodium hypochlorite yields mainly O-isopropyl N-ethylcarbamate. The formation of this compound in wastewaters can be of concern, since simple alkyl carbamates are cancer suspect agents.

Introduction : The value of intravenous thrombolysis (IVT) in patients eligible for mechanical thrombectomy (MT) remains unclear. We hypothesized that pre‐treatment with and/or ongoing IVT may facilitate reperfusion of distal vessel occlusion after incomplete MT. We evaluated this potential association using follow‐up perfusion imaging. Methods : Retrospective observational analysis of our institution`s stroke registry included patients with incomplete reperfusion after MT, admitted between February 1, 2015 and December 8, 2020. Delayed reperfusion (DR) was defined as the absence of a persistent perfusion deficit on contrast‐enhanced perfusion imaging ⁓24h±12h after the intervention. The association between baseline parameters and the occurrence of DR was evaluated using a logistic regression analyses. To account for possible time‐dependent associations of IVT with DR, additional stratification sets were made based on different time windows between IVT start time and final angiography runs. Results : Among the 378 included patients (median age 73.5, 50.8% female), DR occurred in 226 (59.8%). Atrial fibrillation (aOR 2.53 [95% CI 1.34 ‐ 4.90]), eTICI score (aOR 3.79 [95% CI 2.71 ‐ 5.48] per TICI grade increase), and intervention‐to‐follow‐up time (aOR 1.08 [95% CI 1.04 ‐ 1.13] per hour delay) were associated with DR. Dichotomized IVT strata showed no association with DR (aOR 0.75 [95% CI 0.42 ‐ 1.33]), whereas shorter intervals between IVT start and end of the procedure showed a borderline significant association with DR (OR 2.24 [95% CI 0.98 ‐ 5.43, and OR 2.07 [95% 1.06 – 4.31], for 80 and 100 minutes respectively). Patients with DR had higher rates of functional independence (modified Rankin scale 0–2 at 90 days, DR: 63.3% vs PPD: 38.8%; p<0.01) and longer survival time (at 3 years, DR: 69.2% vs PPD: 45.8%; p = 0.001). Conclusions : There is weak evidence that IVT may favor DR after incomplete MT if the time interval between IVT administration and end of the procedure is short. In general, perfusion follow‐up imaging may constitute a suitable surrogate parameter for evaluating medical rescue strategies after incomplete MT, because a considerable proportion of patients do not experience DR, and there seems to be a close correlation with clinical outcomes.

The construction of smooth interpolation trajectories in different non-Euclidean spaces finds application in robotics, computer graphics, and many other engineering fields. This paper proposes a method for generating interpolation trajectories on the special orthogonal group SO(3), called the rotation group. Our method is based on a high-dimensional generalization of the Kuramoto model which is a well-known mathematical description of self-organization in large populations of coupled oscillators. We present the method through several simulations and visualize each simulation as trajectories on unit spheres S2. In addition, we applied our method to the specific problem of object rotation interpolation.

The primary function of the university, in addition to education, is scientific research. At Bosnia and Herzegovina universities, the scientific research has been neglected. There are two basic reasons for that. The first is insufficient financial investment in science and research, and the second is an underdeveloped awareness of the importance of scientific research work, both in the society of Bosnia and Herzegovina and in universities themselves. This paper indicates what needs to be done to overcome this latter difficulty. In addition, the possibilities for improving science and shaping the science system at universities in Bosnia and Herzegovina to make them research universities were analysed. Scientific research work builds on research and development work, technological development, cooperation with the economy and the development of science and technology parks. These activities are even less represented at universities in Bosnia and Herzegovina than scientific research work. This paper shows the ways how to overcome these difficulties, so that research universities become carriers of the technological development of Bosnia and Herzegovina.

Seismological constraints obtained from receiver function (RF) analysis provide important information about the crust and mantle structure. Here, we explore the utility of the free‐surface multiple of the P‐wave (PP) and the corresponding conversions in RF analysis. Using earthquake records, we demonstrate the efficacy of PPs‐RFs before illustrating how they become especially useful when limited data is available in typical planetary missions. Using a transdimensional hierarchical Bayesian deconvolution approach, we compute robust P‐to‐S (Ps)‐ and PPs‐RFs with InSight recordings of five marsquakes. Our Ps‐RF results verify the direct Ps converted phases reported by previous RF analyses with increased coherence and reveal other phases including the primary multiple reverberating within the uppermost layer of the Martian crust. Unlike the Ps‐RFs, our PPs‐RFs lack an arrival at 7.2 s lag time. Whereas Ps‐RFs on Mars could be equally well fit by a two‐ or three‐layer crust, synthetic modeling shows that the disappearance of the 7.2 s phase requires a three‐layer crust, and is highly sensitive to velocity and thickness of intra‐crustal layers. We show that a three‐layer crust is also preferred by S‐to‐P (Sp)‐RFs. While the deepest interface of the three‐layer crust represents the crust‐mantle interface beneath the InSight landing site, the other two interfaces at shallower depths could represent a sharp transition between either fractured and unfractured materials or thick basaltic flows and pre‐existing crustal materials. PPs‐RFs can provide complementary constraints and maximize the extraction of information about crustal structure in data‐constrained circumstances such as planetary missions.

Colorectal cancer (CRC) has the second-highest tumor incidence and is a leading cause of death by cancer. Nearly 20% of patients with CRC will have metastases (mts) at the time of diagnosis, and more than 50% of patients with CRC develop metastases during their disease. Unfortunately, only 45% of patients after a chemotherapy will respond to treatment. The aim of this study is to develop and validate a machine learning algorithm to predict response of individual liver mts, using CT scans. Understanding which mts will respond or not will help clinicians in providing a more efficient per-lesion treatment based on patient specific response and not only following a standard treatment. A group of 92 patients was enrolled from two Italian institutions. CT scans were collected, and the portal venous phase was manually segmented by an expert radiologist. Then, 75 radiomics features were extracted both from 7x7 ROIs that moved across the image and from the whole 3D mts. Feature selection was performed using a genetic algorithm. Results are presented as a comparison of the two different approaches of features extraction and different classification algorithms. Accuracy (ACC), sensitivity (SE), specificity (SP), negative and positive predictive values (NPV and PPV) were evaluated for all lesions (per-lesion analysis) and patients (per-patient analysis) in the construction and validation sets. Best results were obtained in the per-lesion analysis from the 3D approach using a Support Vector Machine as classifier. We reached on the training set an ACC of 81%, while on test set, we obtained SE of 76%, SP of 67%, PPV of 69% and NPV of 75%. On the validation set a SE of 61%, SP of 60%, PPV of 57% and NPV of 64% were reached. The promising results obtained in the validation dataset should be extended to a larger cohort of patient to further validate our method.Clinical Relevance— to develop a radiomics signatures predicting single liver mts response to therapy. A personalized mts approach is important to avoid unnecessary toxicity offering more suitable treatments and a better quality of life to oncological patients.

Automatic segmentation of the prostate on Magnetic Resonance Imaging (MRI) is one of the topics on which research has focused in recent years as it is a fundamental first step in the building process of a Computer aided diagnosis (CAD) system for cancer detection. Unfortunately, MRI acquired in different centers with different scanners leads to images with different characteristics. In this work, we propose an automatic algorithm for prostate segmentation, based on a U-Net applying transfer learning method in a bi-center setting. First, T2w images with and without endorectal coil from 80 patients acquired at Center A were used as training set and internal validation set. Then, T2w images without endorectal coil from 20 patients acquired at Center B were used as external validation. The reference standard for this study was manual segmentation of the prostate gland performed by an expert operator. The results showed a Dice similarity coefficient >85% in both internal and external validation datasets.Clinical Relevance— This segmentation algorithm could be integrated into a CAD system to optimize computational effort in prostate cancer detection.

Breast cancer is the most commonly occurring malignancy and the leading cause of cancer-related death in women. Triple-negative breast cancer (TNBC) is the most aggressive subtype and is associated with high recurrence rates, high incidence of distant metastases, and poor overall survival. The aim of this study was to investigate the PI3K/PTEN/Akt/mTOR pathway as one of the most frequently deregulated pathways in cancer. We aimed to explore the impact of PI3K and mTOR oncogenes as well as the PTEN tumor suppressor on TNBC clinical behavior, prognosis, and multidrug resistance (MDR), using immunohistochemistry and copy number analysis by quantitative real-time PCR. Our results revealed that loss of PTEN and high expression of PI3K and mTOR proteins are associated with poor outcome of TNBC patients. PTEN deletions appeared as a major cause of reduced or absent PTEN expression in TNBC. Importantly, homozygous deletions of PTEN (and not hemizygous deletions) are a potential molecular marker of metastasis formation and good predictors of TNBC outcome. In conclusion, we believe that concurrent examination of PTEN/PI3K/mTOR protein expression may be more useful in predicting TNBC clinical course than the analysis of single protein expression. Specifically, our results showed that PTEN-reduced/PI3K-high/mTOR-high expression constitutes a ‘high risk’ profile of TNBC.

The paper presents the results of modeling the bending strength of wood. During the experimental examination and definition of the model, solid wood was taken, where the bending was performed perpendicular to the grain. The experiment was done with thirteen replications and the input values that varied at three levels were wood density and board thickness. The thirteen-repetition experiment also involved four repetitions in the marginal areas, so two more wood densities and two board thicknesses had to be taken. The experimental measurement was performed in the laboratory of the Technical Faculty Bihać. Based on the experimental results, a sufficiently adequate mathematical model of the breaking force of a solid wood panel perpendicular to the grain is obtained.

Paper presents the design of experiment and determining mathematical model to calculate roughness parameter of wood planned surface. For design of experiment three different types of solid wood were taken and processed on the planner with three different displacements and three different cutting speeds. After measuring the roughness parameter Rz, experimental results were obtained on the basis of which the central composite plan of the experiment was made. Based on that, a model of roughness parameter Rz was made, which is adequate and with high accuracy. The significance of the model coefficients was determined using the R software and the results were presented using the Design Expert software.

Introduction unCoVer—Unravelling data for rapid evidence-based response to COVID-19—is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response and provision of care to patients with COVID-19 by health systems across Europe and elsewhere. unCoVer aims to exploit the full potential of this information to rapidly address clinical and epidemiological research questions arising from the evolving pandemic. Methods and analysis From the onset of the COVID-19 pandemic, partners are gathering RWD from electronic health records currently including information from over 22 000 hospitalised patients with COVID-19, and national surveillance and screening data, and registries with over 1 900 000 COVID-19 cases across Europe, with continuous updates. These heterogeneous datasets will be described, harmonised and integrated into a multi-user data repository operated through Opal-DataSHIELD, an interoperable open-source server application. Federated data analyses, without sharing or disclosing any individual-level data, will be performed with the objective to reveal patients’ baseline characteristics, biomarkers, determinants of COVID-19 prognosis, safety and effectiveness of treatments, and potential strategies against COVID-19, as well as epidemiological patterns. These analyses will complement evidence from efficacy/safety clinical trials, where vulnerable, more complex/heterogeneous populations and those most at risk of severe COVID-19 are often excluded. Ethics and dissemination After strict ethical considerations, databases will be available through a federated data analysis platform that allows processing of available COVID-19 RWD without disclosing identification information to analysts and limiting output to data aggregates. Dissemination of unCoVer’s activities will be related to the access and use of dissimilar RWD, as well as the results generated by the pooled analyses. Dissemination will include training and educational activities, scientific publications and conference communications.

Comprehension of speech in noise is a challenge for hearing-impaired (HI) individuals. Electroencephalography (EEG) provides a tool to investigate the effect of different levels of signal-to-noise ratio (SNR) of the speech. Most studies with EEG have focused on spectral power in well-defined frequency bands such as alpha band. In this study, we investigate how local functional connectivity, i.e. functional connectivity within a localized region of the brain, is affected by two levels of SNR. Twenty-two HI participants performed a continuous speech in noise task at two different SNRs (+3 dB and +8 dB). The local connectivity within eight regions of interest was computed by using a multivariate phase synchrony measure on EEG data. The results showed that phase synchrony increased in the parietal and frontal area as a response to increasing SNR. We contend that local connectivity measures can be used to discriminate between speech-evoked EEG responses at different SNRs.