Nonorthogonal multiple access (NOMA) significantly improves the connectivity opportunities and enhances the spectrum efficiency (SE) in the fifth generation and beyond (B5G) wireless communications. Meanwhile, emerging B5G services demand for higher SE in the NOMA-based wireless communications. However, traditional ground-to-ground (G2G) communications are hard to satisfy these demands, especially for the cellular uplinks. To solve these challenges, this article proposes a multiple unmanned-aerial-vehicles (UAVs)-aided uplink NOMA method. In detail, multiple hovering UAVs relay data for a half of ground users (GUs) and share the spectrums with the other GUs that communicate with the base station (BS) directly. Furthermore, this article proposes a K-means clustering-based UAV deployment scheme and location-based user pairing (UP) scheme to optimize the transceiver association for the multiple UAVs-aided NOMA uplinks. Finally, a sum power minimization-based resource allocation problem is formulated with the lowest Quality-of-Service (QoS) constraints. We solve it with the message-passing algorithm and evaluate the superior performances of the proposed scheduling and paring schemes on SE and energy efficiency (EE). Extensive simulations are conducted to compare the performances of the proposed schemes with those of the single UAV-aided NOMA uplinks, G2G-based NOMA uplinks, and the proposed multiple UAVs-aided uplinks with a facility location framework-based UAV deployment. Simulation results demonstrate that the proposed multiple UAVs deployment and UP-based NOMA scheme significantly improves the EE and the SE of the cellular uplinks at the cost of only a little relaying power consumption of UAVs.

Abstract The goal of this study was to determine the content of 12 metals in 23 samples of teeth from two cities in Bosnia and Herzegovina (B&H): Sarajevo, a capital city with heavy traffic, industrial facilities, and long periods of smog during winter and Bihac, a picturesque small city, with no industrialization, settled among vivid national park and rivers. The teeth were separated into enamel and dentin. Dissolution of samples was performed in concentrated HNO3 with the addition of H2O2 followed by flame atomic absorption spectroscopy (FAAS) analysis. The results showed expected high contents of Ca, Na, Mg, and K, while elevated contents of Cu, Fe, and Zn were present in some samples. K and Na showed uniform distributions throughout enamel and dentin. Alkaline and earth-alkaline metals showed significant positive correlations. Zinc and manganese exhibited differences in the dentin content based on the place of residence. Zinc also displayed statistically significant differences between smokers’ and nonsmokers’ dentin samples. The differences were more pronounced between intra groups (within one sample) than for inter groups (within different groups, such as location, gender, and smoking).

We show that scattering from the boundary of static, higher-order topological insulators (HOTIs) can be used to simulate the behavior of (time-periodic) Floquet topological insulators. We consider D-dimensional HOTIs with gapless corner states which are weakly probed by external waves in a scattering setup. We find that the unitary reflection matrix describing back-scattering from the boundary of the HOTI is topologically equivalent to a (D-1)-dimensional nontrivial Floquet operator. To characterize the topology of the reflection matrix, we introduce the concept of `nested' scattering matrices. Our results provide a route to engineer topological Floquet systems in the lab without the need for external driving. As benefit, the topological system does not to suffer from decoherence and heating.

BACKGROUND The Emergency Severity Index (ESI) is a widely used tool to triage patients in emergency departments. The ESI tool is used to assess all complaints and has significant limitation for accurately triaging patients with suspected acute coronary syndrome (ACS). OBJECTIVE We evaluated the accuracy of ESI in predicting serious outcomes in suspected ACS and aimed to assess the incremental reclassification performance if ESI is supplemented with a clinically validated tool used to risk-stratify suspected ACS. METHODS We used existing data from an observational cohort study of patients with chest pain. We extracted ESI scores documented by triage nurses during routine medical care. Two independent reviewers adjudicated the primary outcome, incidence of 30-day major adverse cardiac events. We compared ESI with the well-established modified HEAR/T (patient History, Electrocardiogram, Age, Risk factors, but without Troponin) score. RESULTS Our sample included 750 patients (age, 59 ± 17 years; 43% female; 40% black). A total of 145 patients (19%) experienced major adverse cardiac event. The area under the receiver operating characteristic curve for ESI score for predicting major adverse cardiac event was 0.656, compared with 0.796 for the modified HEAR/T score. Using the modified HEAR/T score, 181 of the 391 false positives (46%) and 16 of the 19 false negatives (84%) assigned by ESI could be reclassified correctly. CONCLUSION The ESI score is poorly associated with serious outcomes in patients with suspected ACS. Supplementing the ESI tool with input from other validated clinical tools can greatly improve the accuracy of triage in patients with suspected ACS.

Background White spot lesions (WSLs) are a common complication after orthodontic treatment. The aim of this study was to characterize and compare the antimicrobial properties of selenium-containing vs. fluoride-containing orthodontic materials. Material/Methods Antibacterial efficacy of orthodontic materials (SeLECT Defense bonding agent, Adhesive agent, Band Cement, Transbond Plus SEP bonding agent, Transbond Plus Adhesive agent, Fuji I Band cement, Fuji Ortho LC Adhesive agent, Ortho Solo Bonding agent, Transbond XT bonding agent, and Transbond XT primer) was tested with the inhibition of 2 bacterial strains: S. mutans (ATCC 10449) and L. acidophilus (ATCC 4356). The antimicrobial efficacy of the materials was measured by agar diffusion test. The diameters of inhibition zones around each disk were measured in millimeters (mm). Results Materials containing selenium and fluoride showed significant differences from the negative control (both p<0.001). Orthodontic materials containing fluoride as a potential antimicrobial agent showed larger zones of inhibition in total (9.1±2.6 mm), the selenium group was the second-most effective (4.7±4.9 mm), and the group without any potential antimicrobial agent showed the least antimicrobial effect (0.9±1.0 mm). Materials from the group with no antibacterial agent were not significantly different from the negative control group (p>0.05). Conclusions Materials containing selenium carried the most significance when comparing microorganisms with the agent, since they were the only ones showing difference between the 2 microorganisms. They showed statistically significant difference in efficacy against S. mutans, and poor antimicrobial effect against L. acidophilus. These data suggest that orthodontic materials containing selenium might have the potential to prevent WSLs due to their antimicrobial properties.

Abstract Wine fermentation is a complex process driven by yeasts, which influence the key properties of wine quality: aroma, flavour and colour. We investigated 95 different Saccharomyces and non-Saccharomyces strains for their impact on wine colour through the synthesis of the stable pigments, pyranoanthocyanins. All strains were screened for their hydroxycinnamate decarboxylase (HCDC) activity that varied from 0.0% to 91.1%. Eight strains that showed more than 40% HCDC activity were further studied for vinylphenolic pyranoanthocyanin formation. Fermentations were carried out in deep well microtiter plates using synthetic grape must containing Pinot Noir skin extract supplemented with p-coumaric acid. Two strains Pichia guilliermondii ZIM624 and Wickerhamomyces anomalus S138 synthesized vinylphenolic pyranoanthocyanins in the highest concentration in single culture fermentations, 40.2 and 38.5 mg L−1, respectively. The highest produced concentration of vinylphenolic pyranoanthocyanins in co-inoculation experiments was 16.4 mg L−1 compared to 29.8 mg L−1 in sequential fermentations. For the first time, S. paradoxus strains were assessed for pyranoanthocyanin formation. Selected strains were also tested as mono-cultures for adsorption of anthocyanins on yeast cell walls and all strains showed anthocyanin and pyranoanthocyanin adsorption to their cell wall with Metschnikowia reukafii ZIM2019 showing the highest adsorbing capability (9.1%).

Like early work on human intergroup interaction, previous research on people’s willingness to interact with robots has focused mainly on effects of anxiety. However, existing findings suggest that other negative emotions as well as some positive emotions also have effects. This article systematically examines the roles of positive and negative emotions in predicting willingness to interact with robots, using an integrative analysis of data across five studies that use diverse interaction conditions and several types of robots. We hypothesize and find that positive emotions account for more variance than negative emotions. Practically, the findings suggest new strategies for interventions, aimed at increasing positive emotions to increase willingness to engage in intergroup interaction. No existing work has examined whether positive emotions are stronger predictors than negative emotions for willingness for human intergroup interaction, an important topic for future research.

ADINA ELENA STANCIU, NAFIJA SERDAREVIC, MARCEL MARIAN STANCIU*, LAURA MAZILU, OVIDIU BRATU , MIRELA GHERGHE, SILVIU CRISTIAN VOINEA, DAN CRISTIAN GHEORGHE Institute of Oncology Bucharest, Department of Carcinogenesis and Molecular Biology, 252 Fundeni, 022338, Bucharest, Romania Institute for Clinical Chemistry and Biochemistry, University of Sarajevo Clinics Center, Bolnicka 25, 71000, Sarajevo, Bosnia and Herzegovina University Politehnica of Bucharest, Electrical Engineering Faculty, 313 Splaiul Independentei, 060042, Bucharest, Romania University Ovidius Constanța, Faculty of Medicine, 124 Mamaia Str., 900527, Constanța, Romania Carol Davila University of Medicine and Pharmacy, 8 Eroii Sanitari, 050474, Bucharest, Romania

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With the edge computing becoming an increasingly adopted concept in system architectures, it is expected its utilization will be additionally heightened when combined with deep learning (DL) techniques. The idea behind integrating demanding processing algorithms in Internet of Things (IoT) and edge devices, such as Deep Neural Network (DNN), has in large measure benefited from the development of edge computing hardware, as well as from adapting the algorithms for use in resource constrained IoT devices. Surprisingly, there are no models yet to optimally place and use machine learning in edge computing. In this paper, we propose the first model of optimal placement of Deep Neural Network (DNN) Placement and Inference in edge computing. We present a mathematical formulation to the DNN Model Variant Selection and Placement (MVSP) problem considering the inference latency of different model-variants, communication latency between nodes, and utilization cost of edge computing nodes. We evaluate our model numerically, and show that for low load increasing model co-location decreases the average latency by 33% of millisecond-scale per request, and for high load, by 21%.