disciplines and research areas that rely on participants’ self-reports to accrue data on participants’ true preferences are faced with the

In this work, we adopt the analysis of a heterogeneous cellular network by means of stochastic geometry, to estimate energy and spectral network efficiency. More specifically, it has been the widely spread experience that practical field assessment of the Signal-to-Noise and Interference Ratio (SINR), being the key physical-layer performance indicator, involves quite sophisticated test instrumentation that is not always available outside the lab environment. So, in this regard, we present here a simpler test model coming out of the much easier-to-measure Bit Error Rate (BER), as the latter can deteriorate due to various impairments regarded here as equivalent with additive white Gaussian noise (AWGN) abstracting (in terms of equal BER degradation) any actual non-AWGN impairment. We validated the derived analytical model for heterogeneous two-tier networks by means of an ns3 simulator, as it provided the test results that fit well to the analytically estimated corresponding ones, both indicating that small cells enable better energy and spectral efficiencies than the larger-cell networks.

Background Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds. Crowdsourcing from social media like Twitter can be used for generating ideas in a noticeably brief time based on contributions from globally distributed users. The world has been challenged by the COVID-19 pandemic in the last several years. Measures to combat the pandemic continue to evolve worldwide, and ideas and opinions on optimal counteraction strategies are of high interest. Objective This study aimed to validate the use of Twitter as a crowdsourcing platform in order to gain an understanding of public opinion on what measures can help to end the COVID-19 pandemic faster. Methods This cross-sectional study was conducted during the period from December 22, 2021, to February 4, 2022. Tweets were posted by accounts operated by the authors, asking “How to faster end the COVID-19 pandemic?” and encouraging the viewers to comment on measures that they perceive would be effective to achieve this goal. The ideas from the users' comments were collected and categorized into two major themes – personal and institutional measures. In the final stage of the campaign, a Twitter poll was conducted to get additional comments and to estimate which of the two groups of measures were perceived to be important amongst Twitter users. Results The crowdsourcing campaign generated seventeen suggested measures categorized into two major themes (personal and institutional) that received a total of 1,727 endorsements (supporting comments, retweets, and likes). The poll received a total of 325 votes with 58% of votes underscoring the importance of both personal and institutional measures, 20% favoring personal measures, 11% favoring institutional measures, and 11% of the votes given just out of curiosity to see the vote results. Conclusions Twitter was utilized successfully for crowdsourcing ideas on strategies how to end the COVID-19 pandemic faster. The results indicate that the Twitter community highly values the significance of both personal responsibility and institutional measures to counteract the pandemic. This study validates the use of Twitter as a primary tool that could be used for crowdsourcing ideas with healthcare significance.

This paper presents the results of a two-year study of six selected soybean genotypes with the aim of examining which of the genotypes in the given production conditions give the best results in regards with the amount and quality of seed yield. All genotypes belong to a zero-maturity group. The correlation between the grain yield per plant and other studied traits was tested through linear (simple) correlations. The testing showed that the following traits had a positive highly significant impact on seed yield: the number of seeds per plant (0.917**), seed germination energy (0.897**), seed moisture content (0.803**), plant height (0.802**), seed germination (0.789**), the number of seeds in pods (0.696**), the number of harvested plants per m-2 (0.590**), the number of plants (phenophase 1-3 in the three-leaf stage) per m2 (0.550**), 1000 seed mass (0.471**), and the height to the first node (0.412**).

Malware traffic classification (MTC) is a key technology for anomaly and intrusion detection in secure Industrial Internet of Things (IIoT). Traditional MTC methods based on port, payload, and statistic depend on the manual-designed features, which have low accuracy. Recently, deep-learning methods have attracted a significant attention due to their high accuracy in terms of classification. However, in practical application scenarios, deep-learning methods require a large amount of labeled samples for training, while the available labeled samples for training are very rare. Furthermore, the preparation of a large amount of labeled samples requires a lot of labor costs. To solve these problems, this article proposes three methods based on semisupervised learning (SSL), transfer learning (TL), and domain adaptive (DA), respectively. Our proposed methods use a large amount of unlabeled data collected in the Internet traffic, which can greatly improve the classification accuracy with few labeled samples. Then, we use the DA method to solve the mismatch problem between the source domain and the target domain in the TL process. The proposed method is not only applicable to the shallow network but also to the deep neural network structure, and can achieve better classification results. Experimental results show that our proposed methods can satisfy the requirement of MTC in the case of few labeled samples in IIoT. The source code for all the experiments is available at GitHub.The code of this article can be downloaded from GitHub link: https://github.com/yzjh/Keras-MTC-DA-Ladder.

We propose a certainty-equivalence scheme for adaptive control of scalar linear systems subject to additive, i.i.d. Gaussian disturbances and bounded control input constraints, without requiring prior knowledge of the bounds of the system parameters, nor the control direction. Assuming that the system is at-worst marginally stable, mean square boundedness of the closed-loop system states is proven. Lastly, numerical examples are presented to illustrate our results.

Abstract Lesser mole-rats (Nannospalax leucodon) are members of the Rodentia order’s Spalacidae family, and they are found in Northeastern Africa, the Balkans, Southeastern Europe, Central Asia, the Middle East, and Caucasia. The shape of the skull has a significant impact on the phenotypic appearance of animal heads, and although many domestic species have been studied, there is a lack of evidence on the macro-anatomical characteristics of the skeletal system in mole-rats. The current research was focused on the morphological, morphometric, and radiographic properties of lesser mole-rats skull in Bosnia and Herzegovina. The research was conducted on five lesser mole-rats from Bjelasnica Mountain, Bosnia and Herzegovina. We compared the results of the previously published studies, and we found a lot of similarities between Nannospalax leucodon in Bosnia and Herzegovina and Nannospalax ehrenbergi in North Iraq, as well as the Nannospalax nehringi from Eastern Anatolia.

Key Points • Rondaptivon pegol is a first-in-class prohemostatic molecule that prolongs the half-life of both endogenous FVIII and substituted FVIII.• Rondaptivon pegol could be used to enable once-weekly substitution therapy in severe hemophilia A or as prophylaxis in nonsevere hemophilia A.

Cyber-physical systems (CPSs) are often complex and safety-critical, making it both challenging and crucial to ensure that the system’s specifications are met. Simulation-based falsification is a practical testing technique for increasing confidence in a CPS’s correctness, as it only requires that the system be simulated. Reducing the number of computationally intensive simulations needed for falsification is a key concern. In this study, we investigate Bayesian optimization (BO), a sample-efficient approach that learns a surrogate model to capture the relationship between input signal parameterization and specification evaluation. We propose two enhancements to the basic BO for improving falsification: (1) leveraging local surrogate models, and (2) utilizing the user’s prior knowledge. Additionally, we address the formulation of acquisition functions for falsification by proposing and evaluating various alternatives. Our benchmark evaluation demonstrates significant improvements when using local surrogate models in BO for falsifying challenging benchmark examples. Incorporating prior knowledge is found to be especially beneficial when the simulation budget is constrained. For some benchmark problems, the choice of acquisition function noticeably impacts the number of simulations required for successful falsification.

PurposeThe study provides the emergence and evolution of the socioemotional wealth (SEW) concept in the family business field from 2007 (the inception date) until 2021. To provide a better overview of this notion, the study unfolds a deeper understanding of this term throughout the systematic literature review (SLR).Design/methodology/approachThe study applies a systematic literature review (SLR) by analyzing the sample of 185SEW articles extracted from the Scopus database. To identify all relevant studies, the article selection process was carefully designed and divided into two phases with clear steps: identification of studies via databases and identification of studies via previous studies' reference lists. Selected studies were analyzed using the Bibliometrix R-tool, resulting in an analysis of the evolution of the trends in the SEW literature, citation analysis, and network analysis. Finally, this SLR included the content analysis of the 25 most-cited SEW articles.FindingsThe study provides a relevant and comprehensive overview facilitating empirical and theoretical research in this field and paving the way to develop new themes. The bottom line of the important findings is that the SEW concept is relatively new, alluding to a wealthy venue for future works. Other results and implications are discussed on the family business and SEW theme. Additionally, the study provides suggestions which could be used for future works in this area.Originality/valueThis is the first article related to the SEW concept in the family business. It portrays a clear picture of this field, providing relevant information on what has been done, as well as what the future possibilities are that might bode the future horizons in family businesses.

The avant-garde approach in the processing of dramatic motifs in the literary work of Miodrag Žalica once pointed to the possibility of a different and more modern expression in Bosnian drama production. Miodrag Žalica›s artistic expression shows an obvious change in the structuring of the play, as well as in the stylistic orientations, which made him the reference writer of the late modern era in Bosnia and Herzegovina. This work presents a review of the positioning of Miodrag Žalica within the framework of modern literary and theatrical aspirations. “Poetically colored meditation”, dramatic characters of the universal type and the choice of themes have provided him with a prominent place in our dramatic literature.