The paper deals with the phenomenon of non-fungible tokens (NFT), and its particular focus is on the so-called “Art NFTs”, and on the legal demystification of the superior attributes assigned to these tokens. The paper addresses a number of issues. Firstly, it examines the legal and technical possibility to actually create a “digitally unique” piece of author’s work. Secondly, it explores the acquisition of ownership and copyright in the work of art, to which the NFT referres to, during the process of creation and transfer of that NFT. Finally, the paper scrutinizes the topics of copyright violations, which may occur while minting the tokens and of the destruction of the physical original of the tokenized work. The paper also deals with two relevant cases from practice (Miramax, LLC v. Tarantino and Free Comb With Pagoda, J.M. Basquiat), which illustrate how the so-called “Art NFTs” collide with copyright principles.

Introduction: As a result of research conducted globally, experts continue to extensively study the long-term consequences that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections can have on patients, as well as the factors contributing to severe outcomes. The aim of this study was to investigate the values of basic biochemical and hematological parameters in patients with fatal outcomes of SARS-CoV-2 infection, as well as to determine the combination of hematological and biochemical parameters that contribute to the progression of SARS-CoV-2 infection. The examined parameters were correlated with the age and gender distribution of patients with fatal outcomes from the SARS-CoV-2 infection. Methods: The study represents a retrospective study of patients hospitalized at the Cantonal Hospital Zenica from February to April 2021, focusing on the biochemical and hematological parameters of subjects with confirmed presence of the SARS-CoV-2 virus using the reverse transcription-polymerase chain reaction methods who were hospitalized at the Cantonal Hospital Zenica. Results: Of the 250 deceased subjects in the sample, females comprised the relative majority at 53.6%. Among the examined parameters, hemoglobin, mean corpuscular hemoglobin (MCH), and MCH were significantly lower in females compared to males, while males had significantly higher values of urea, creatinine, and troponin. The average age of the patients was 74 years, and with aging, the values of erythrocytes, hemoglobin, and troponin increased. Troponin showed a statistically significant positive correlation with age, as well as with urea and creatinine. Conclusion: We can conclude that hemoglobin, urea, creatinine, and troponin are parameters that can be considered to contribute to the progression of SARS-CoV-2 infection. These parameters can be useful for assessing disease severity and prognosis in patients infected with the SARS-CoV-2 virus.

Abstract Online shopping helps consumers search for information about products and services, makes it easier to compare prices and product features, and enables a quick and easy exchange of positive and negative experiences. However, through numerous positive advantages, there is inevitably a constant increase in the negative consequences of online shopping, especially from the consumer's perspective.

Abstract The paper aims to identify the possibility of positioning the profession of forensic accountant in the financial sector of the Federation of Bosnia and Herzegovina (hereinafter FBiH). To answer the question of how the profession of forensic accountant could be introduced into the financial sector, qualitative research was conducted using the method of interviews with respondents who have many years of experience in the financial sector of FBiH.

To provide seamless wireless coverage, the air-to-ground (A2G) heterogeneous wireless network is considered as one of the most promising solutions. In this article, we develop a novel A2G communication-caching-charging (3C) integrated network based on non-orthogonal multiple access (NOMA). As a significant participant of A2G network, unmanned aerial vehicle (UAV), which harvests energy from the base station (BS) with the aid of wireless power transfer (WPT), is utilized as content server to cache files and serve users. To be specific, we first propose a resource allocation strategy to enhance the quality of service (QoS) of ground users. The goal is to minimize the transmission latency of ground users, which is decomposed into sub-problems, such as user pairing, files' power allocation and users' power allocation. Firstly, we propose a NOMA user pairing algorithm based on K-means to deploy UAVs and pair users. Then, the closed-form solution for files' power allocation with the goal of maximizing the duration for energy harvesting is formulated. Finally, we apply the genetic algorithm (GA) to obtain power allocation factors to increase users' rate and the reminder time of content delivery phase is utilized for energy harvesting. Simulation results validate the advantage of the proposed strategy in reducing user delay than benchmark schemes.

To establish more intelligent cellular networks for future ubiquitous access and heterogeneous devices, we need to obtain channel state information (CSI) in a more agile and economical manner, especially for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) architectures. Unlike conventional CSI feedback or limited feedback methods, we can predict downlink CSI by leveraging channel reciprocity between uplink and downlink. The downlink CSI prediction can be formulated as a data-driven deep learning task, however, there exist isolated data silos and online adaptation problem for the offline trained neural network-based models. In this article, we propose an interacting federated and transfer learning (IFTL) based framework for downlink CSI prediction and online update, where several factors including asynchrony of different clients are considered, and light heterogeneity of diverse cells can be tolerated. Both model-level and link-level simulations are conducted under standardized FDD massive MIMO scenarios. The results outline promising prospect and potential of the utilization of federated learning and transfer learning in physical layer of wireless communications.

Specific emitter identification (SEI) is a potential physical layer authentication technology, which is one of the most critical complements of upper layer authentication. Radio frequency fingerprint (RFF)-based SEI is to distinguish one emitter from each other by immutable RF characteristics from electronic components. Due to the powerful ability of deep learning (DL) to extract hidden features and perform classification, it can extract highly separative features from massive signal samples, thus enabling SEI. Considering the condition of limited training samples, we propose a novel few-shot SEI (FS-SEI) method based on interpolative metric learning (InterML) which gets rid of the dependence on auxiliary dataset. Specifically, InterML is designed to mine more implicit samples in the sample space to improve generalization, and constrain the feature distance in the feature space to improve discriminability. The proposed InterML-based FS-SEI method is evaluated on a real-world Wi-Fi dataset. The simulation results show that the proposed method achieves better identification performance, higher feature discriminability and more stable performance than five latest FS-SEI methods. In the 10 shot scenario, the identification accuracy of InterML is 91.48%, compared to the comparison methods, the accuracy is improved by 0.62%–31.29%.

In this article, we propose a few-shot indoor position method based on Triplet Matchnet, which transforms coordinate positioning into channel state information (CSI) similarity matching problem. Triplet loss is designed to train and learn hidden correspondence between CSI features and physical space positions, with emphasis on minimizing distance or angle-based triplet loss. Then, according to pre-trained network with best similarity match, a similarity score map of CSI with unknown coordinates is constructed to predict position precisely. Experimental results show that angle-based triplet loss can obtain more accurate CSI fingerprint similarity matching accuracy. Compared with existing methods, experiment results confirm that our proposed method can achieve excellent positioning performance with few-shot datasets.

BACKGROUND To assess 28-day survival in two pilot groups of septic shock patients with euthyroid sick syndrome (ESS) supplemented with triiodothyronine (T3). METHODS A total of 95 septic shock patients with ESS were divided according to values of the thyroid hormones into low T3 and low T3T4 groups. Among 48 patients with low T3, 24 (50%) were randomized to T3 for 4 days and 24 (50%) to placebo. Among 47 patients with low T3T4, 24 (51%) were randomized to T3 for 4 days and 23 (49%) to placebo. The analysis included 28-day survival as the primary outcome and laboratory with hemodynamics as the secondary outcome. Laboratory data were analyzed on the day of admission (t0), on the first (t1), third (T2) and seventh day (t3) with hemodynamics analyzed for the first four days. RESULTS In the low T3 population, 18 (75%) patients receiving T3 died at day 28 compared with 8 (33.3%) patients receiving placebo (p = 0.004). In the low T3T4 population, 6 (25%) patients receiving T3 died in ICU compared with 12 (52.1%) patients receiving placebo (p = 0.039). Oral T3 treatment increased mean arterial pressure values at day 1, day 3 and day 7 in the low T3T4 population, (p = 0.015, =0.005 and =0.042 respectively), and had no significant effect on these values in the low T3 population. CONCLUSION T3 supplementation was associated with a low 28-day mortality rate in patients with low T3T4 but with increased mortality in patients with low T3 ESS. These results suggest caution before initiating thyroid supplementation in septic patients. REGISTRATION ClinTrials.gov (NCT05270798).