Miracle-dz/UniFAR-FTUs huggingface dataset:
Controller synthesis for discrete‐time positive switched T–S fuzzy systems with partially controllable subsystems

The controller synthesis problem for discrete‐time positive switched T–S fuzzy systems (PSTSFSs) is investigated in this paper. Unlike previous literature, subsystems are assumed to be partially controllable in this paper. A novel slow–fast combined mode‐dependent average dwell time (SFCMDADT) approach is proposed to obtain sufficient conditions for the stability of general positive switched nonlinear systems with partially stable subsystems. Then based on the obtained results, a parallel distributed compensation (PDC)‐based fuzzy controller is designed, and sufficient conditions for the stability of PSTSFSs with partially controllable subsystems are developed with the aid of a time‐scheduled multiple linear copositive Lyapunov function. Furthermore, sufficient conditions for the stability of the positive switched T–S fuzzy system are given respectively for the two cases that the subsystems are all controllable and all uncontrollable. Finally, two simulation examples are provided to illustrate the effectiveness of the proposed method.
Hybrid analysis for understanding contact tracing apps adoption

PurposeThis study aims to explore the adoption of contact tracing apps through a hybrid analysis of the collected data using structural equation modelling (SEM) and artificial neural networks (ANN), leading to the identification of the critical determinants for the adoption of contact tracing apps in Australia.Design/methodology/approachA research model is developed within the background of the unified theory of acceptance and use of technology (UTAUT) and the privacy calculus theory (PCT) for investigating the adoption of contact tracing apps. This model is then tested and validated using a hybrid SEM-ANN analysis of the survey data.FindingsThe study shows that effort expectancy, perceived value of information disclosure and social influence are critical for adopting contact tracing apps. It reveals that performance expectancy and perceived privacy risks are indirectly significant on the adoption through the influence of perceived value of information disclosure. Furthermore, the study finds out that facilitating condition is insignificant to the adoption of contact tracing apps.Practical implicationsThe findings of the study can lead to the formulation of targeted strategies and policies for promoting the adoption of contact tracing apps and inform future epidemic control for better emergency management.Originality/valueThis study is the first attempt in integrating UTAUT and PCT for exploring the adoption of contact tracing apps in Australia. It combines SEM and ANN for analysing the survey data, leading to better understanding of the critical determinants for the adoption of contact tracing apps.
Estimating the Polytropic Indices of Plasmas with Partial Temperature Tensor Measurements: Application to Solar Wind Protons at ~1 au

We examine the relationships between temperature tensor elements and their connection to the polytropic equation, which describes the relationship between the plasma scalar temperature and density. We investigate the possibility to determine the plasma polytropic index by fitting the fluctuations of temperature either perpendicular or parallel to the magnetic field. Such an application is particularly useful when the full temperature tensor is not available from the observations. We use solar wind proton observations at ~1 au to calculate the correlations between the temperature tensor elements and the scalar temperature. Our analysis also derives the polytropic equation in selected streamlines of solar wind plasma proton observations that exhibit temperature anisotropies related to stream-interaction regions. We compare the polytropic indices derived by fitting fluctuations of the scalar, perpendicular, and parallel temperatures, respectively. We show that the use of the parallel or perpendicular temperature, instead of the scalar temperature, still accurately derives the true, average polytropic index value, but only for a certain level of temperature anisotropy variability within the analyzed streamlines. The use of the perpendicular temperature leads to more accurate calculations, because its correlation with the scalar temperature is less affected by the anisotropy fluctuations.
What Leaders Say versus What They Do: Inclusive Leadership, Policy-Practice Decoupling, and the Anomaly of Climate for Inclusion

Inclusion is increasingly recognized as a critical leadership issue, yet research points to effectiveness variability among diversity and inclusion initiatives, indicative of potential policy-practice decoupling. Drawing on climate theory, we develop supervisors’ inclusive leadership and climate for inclusion and introducing CEO’s inclusive leadership and group diversity as moderators. To gain a deep understanding of decoupling, we use a multilevel approach and include in our model both top level leadership (CEOs), where espoused policies are determined, and group level leadership (supervisor), where enacted behaviors are experienced. We offer a novel perspective on climate theory for inclusion, which we have identified as “the anomaly of climate for inclusion. ” Unlike other organizational climate facets, inclusion climate is shaped not only by the shared experiences of group members but also by their identities. Individuals from minority or underrepresented groups might experience decoupling in ways that are similar to other members from the same identity group even if they belong to different work groups. Our model, therefore, explains the process in which leaders create inclusive climate and point to boundary conditions in the process. We focus on two climate indicators: climate level and climate strength, and indicate that both are essential for understanding inclusion climate. Our conceptual model suggests that truly inclusive leaders would succeed at minimizing policy-practice coupling as perceived by all group members, not just historically dominant or high-status members. Implications for practice and future research are discussed.
Anti-reproductive efficacy of Adansonia digitata Powder against Dinoderus porcellus Associated with Yam Chips Spoilage in Jos Metropolis, Nigeria

This study assessed the reproduction inhibition effects of Adansonai digitata plant part powders against D. porcellus affecting yam chips. Reproduction of adults D. porcellus were monitored with various doses of Adansonai digitata plant part powders and untreated yam chips as negative control (0 g). The finding of the research indicated that all treatments exhibited anti-reproduction potential and strong inhibition of D. porcellus emergence. The result of analysis of variance showed significant difference between the treated samples and the control (untreated) after 37 days. Adansonai digitata stem bark powders (10 g) was able to achieve no reproduction (0.00) after 37 days exposure. Based on this results, combining yam chips with 10 g of Adansonai digitata stem bark powders could ensure adequate management of D. porcellus destroying yam chips and yam tubers as a whole. DOI: https://dx.doi. org/10.4314/jasem.v25i2. 19 Copyright: Copyright © 2021 John et al. This is an open access article distributed under the Creative Commons Attribution License (CCL), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Dates: Received: 12 December 2020; Revised: 26 January 2021; Accepted: 12 February 2021
Design and Control of a Novel Coaxial Tilt-Rotor UAV

In this article, the design and control of a new coaxial tilt-rotor unmanned aerial vehicle (CTRUAV) are presented. The CTRUAV is an electric-powered unmanned aerial vehicle with a special configuration, which is composed of two pairs of tiltable coaxial rotors and a rear rotor. A CTRUAV prototype has been designed by 3-D computer-aided design software and constructed according to the designing scheme. The dynamic model of a CTRUAV is derived by utilizing the Euler–Lagrange equation, which considers the special features of the coaxial rotors and air drag forces on the CTRUAV. An adaptive controller is developed to realize motion control for the CTRUAV. The adaptive controller includes two subcontrollers: an inner-loop attitude controller and an outer-loop velocity controller. The stability of the resulting closed-loop CTRUAV system is analyzed via the Lyapunov method. Finally, several simulations and real experimental tests are implemented to validate the effectiveness of the developed CTRUAV system.
X-RAY SPECTROMETRY FROM A MICROCT SYSTEM

X-ray production is of fundamental importance for several applications, among these is the Microcomputed tomography technique (microCT). It is used to conduct studies in different areas of research such as industry, dentistry, archaeology and biomedicine. In this study, X-ray spectra were acquired with different filtering configurations in order to better understand the energy behavior of a X-ray beam used in a microCT system. Unfiltered spectra were acquired for voltages of 20 up to 80 kV and filtered spectra for voltages from 40 up to 120 kV. As results, the mean energy values of each filtered and unfiltered beams from 40 to 120 kV were obtained. These values were calculated based on the spectra evaluation, as well as the value of attenuation that each filtering systems generated in the spectra of 60 and 70 kV. To compose the filtration systems metallic physical filters of aluminum and copper were used. Spectra acquisition was done using a semiconductor detector, model XR-100CdTe, manufactured by Amptek.
The Relationship Between Response Probabilities and Data Quality in Grid Questions

Response probabilities are used in adaptive and responsive survey designs to guide data collection efforts, often with the goal of diversifying the sample composition. However, if response probabilities are also correlated with measurement error, this approach could introduce bias into survey data. This study analyzes the relationship between response probabilities and data quality in grid questions. Drawing on data from the probability-based GESIS panel, we found low propensity cases to more frequently produce item nonresponse and nondifferentiated answers than high propensity cases. However, this effect was observed only among long-time respondents, not among those who joined more recently. We caution that using adaptive or responsive techniques may increase measurement error while reducing the risk of nonresponse bias.
Utility of Multidetector Computed Tomographic Angiography as an Alternative to Transesophageal Echocardiogram for Preoperative Transcatheter Mitral Valve Repair Planning

BACKGROUND Three-dimensional (3D) transesophageal echocardiogram (TEE) is the gold standard for the diagnosis of degenerative mitral regurgitation (dMR) and preoperative planning for transcatheter mitral valve repair (TMVr). TEE is an invasive modality requiring anesthesia and esophageal intubation. The severe acute respiratory syndrome coronavirus 2 pandemic has limited the number of elective invasive procedures. Multi-detector computed tomographic angiography (MDCT) provides high-resolution images and 3D reconstructions to assess complex mitral anatomy. We hypothesized that MDCT would reveal similar information to TEE relevant to TMVr, thus deferring the need for a preoperative TEE in certain situations like during a pandemic. METHODS We retrospectively analyzed data on patients who underwent or were evaluated for TMVr for dMR with preoperative MDCT and TEE between 2017 and 2019. Two TEE and 2 MDCT readers, blinded to patient outcome, analyzed: leaflet pathology (flail, degenerative, mixed), leaflet location, mitral valve area (MVA), flail width/gap, anterior-posterior (AP) and commissural diameters, posterior leaflet length, leaflet thickness, presence of mitral valve cleft and degree of mitral annular calcification (MAC). RESULTS A total of 22 (out of 87) patients had preoperative MDCT. MDCT correctly identified the leaflet pathology in 77% (17/22), flail leaflet in 91% (10/11), MAC degree in 91% (10/11) and the dysfunctional leaflet location in 95% (21/22) of patients. There were no differences in the measurements for MVA, flail width, commissural or AP diameter, posterior leaflet length, and leaflet thickness. MDCT overestimated the measurements of flail gap. CONCLUSIONS For preoperative TMVr planning, MDCT provided similar measurements to TEE in our study.
DIMI: Detecção Inteligente de Botnets Mirai em Redes IoT

The emerging usage of Internet of Things (IoT) paradigm brings,together with new services, new threats to Information Security.Among these threats, we have the Mirai Botnet that performed severalDistributed Denial of Service (DDoS) cyberattacks, exploringthe vulnerabilites of IoT devices. Within this context, this paperpresents a mechanism for detecting Mirai botnet attacks on IoTnetworks using ML techniques and comparing different approaches.The mechanism was evaluated using a set of traffic data from realIoT devices, achieving results with 99 % precision in detecting MiraiBotnet attacks.
Understanding the connection between the ‘Āina, strengths, and houselessness among previously houseless Native Hawaiian and Micronesian families

ABSTRACT Houselessness in Hawai‘i is a structural public health concern, and strategies are needed to address the issue. Using a strength-based approach, this study sought to examine protective factors within a family resilience framework for formerly houseless Native Hawaiian and Micronesian families. Through in-depth, qualitative interviews with previously houseless Native Hawaiian and Micronesian families, this study explored both challenges and protective factors. The data were coded using the coding and themes based on previous research that developed a framework for family resilience. The study found that the families did utilize many of the protective factors in the theoretical framework. The study also uncovered a strong connection to the ‘āina and the impact of historical trauma. Implications for strength-based interventions and further research are discussed.
Machine Learning in International Trade Research: Evaluating the Impact of Trade Agreements

Modern trade agreements contain a large number of provisions besides tariff reductions, in areas as diverse as services trade, competition policy, trade-related investment measures, or public procurement. Existing research has struggled with overfitting and severe multicollinearity problems when trying to estimate the effects of these provisions on trade flows. In this paper, we develop a new method to estimate the impact of individual provisions on trade flows that does not require ad hoc assumptions on how to aggregate individual provisions. Building on recent developments in the machine learning and variable selection literature, we propose data-driven methods for selecting the most important provisions and quantifying their impact on trade flows. We find that provisions related to antidumping, competition policy, technical barriers to trade, and trade facilitation are associated with enhancing the trade-increasing effect of trade agreements.
Sufficient number of replications for path analysis in maize

The number of replications is assumed to interfere in the estimates of the path analysis coefficients. Thus, the objective of this work was to determine the sufficient number of replications for the path analysis of traits in maize cultivars. An experiment was conducted with 15 maize cultivars in a complete randomized block design with nine replications, and seven variables were measured. Then, 511 data files (matrices) formed by all combinations of the nine replications were organized, in groups of 1, 2, 3, 4, 5, 6, 7, 8 and 9 replications. In each matrix, containing the averages of 15 cultivars for the seven variables, Pearson's linear correlation coefficients were estimated, the multicollinearity diagnostics and path analysis were performed and dispersion diagrams were constructed. The sufficient number of replications for the path analysis was determined from the parameter estimates of the quadratic response plateau model. With the replications number increases, the accuracy of the path analysis coefficient estimates improves, but the gains in accuracy gradually decrease. Six replications are sufficient to perform the path analysis of agronomic traits of maize cultivars and can be used as a reference for designing future experiments.
Genetic architecture and heritability of early‐life telomere length in a wild passerine

Early‐life telomere length (TL) is associated with fitness in a range of organisms. Little is known about the genetic basis of variation in TL in wild animal populations, but to understand the evolutionary and ecological significance of TL it is important to quantify the relative importance of genetic and environmental variation in TL. In this study, we measured TL in 2746 house sparrow nestlings sampled across 20 years and used an animal model to show that there is a small heritable component of early‐life TL (h2 = 0.04). Variation in TL among individuals was mainly driven by environmental (annual) variance, but also brood and parental effects. Parent‐offspring regressions showed a large maternal inheritance component in TL ( hmaternal2 = 0.44), but no paternal inheritance. We did not find evidence for a negative genetic correlation underlying the observed negative phenotypic correlation between TL and structural body size. Thus, TL may evolve independently of body size and the negative phenotypic correlation is likely to be caused by nongenetic environmental effects. We further used genome‐wide association analysis to identify genomic regions associated with TL variation. We identified several putative genes underlying TL variation; these have been inferred to be involved in oxidative stress, cellular growth, skeletal development, cell differentiation and tumorigenesis in other species. Together, our results show that TL has a low heritability and is a polygenic trait strongly affected by environmental conditions in a free‐living bird.
Assessing patterns of genetic diversity and connectivity among guanacos (Lama guanicoe) in the Bolivian Chaco: implications for designing management strategies

ABSTRACT Although guanacos (Lama guanicoe) are widely distributed throughout much of their historic range, they are often restricted to small, isolated populations that are at risk of inbreeding and loss of genetic diversity. Here we document and interpret baseline patterns of genetic variation in a guanaco population inhabiting in the Bolivian Chaco that is threatened by hunting and habitat degradation. The region, once open grasslands, is dominated by dense shrubs, the result of livestock grazing. The most-recent census identified only 74 individuals and is designated as at ‘risk of extinction’ by the Bolivian government. We assessed the population’s genetic health and uniqueness from the genetic patterns of 16 microsatellite loci, the Hyper-variable Domain I of the mitochondrial Control Region and SRY gene with 29 fecal samples. We identified 19 male and 10 female unique individuals. Microsatellite variation (Ho = 0.64) was similar to larger, less-isolated populations. However, the estimated effective population size was low and consistent with the continuing loss of allelic variation. The two observed mtDNA haplotypes are common in other L. g. guanicoe populations. Although we documented moderate genetic diversity, gene flow among Bolivian and Paraguayan guanaco Chaco populations should be assessed and integrated into explicit conservation management plans.
How weather conditions affect guest arrivals and duration of stay: An alpine destination case

Funding information German Federal Ministry of Environment, Nature Protection and Nuclear Safety, Grant/ Award Number: 3717 48 107 0 Abstract Weather can be a major concern for travelers when choosing a destination, preparing their trip and during their stay. Existing publications focus on explaining the role of weather based on one, or at most, a few parameters and usually for one season. This paper proposes a new approach covering all four seasons by connecting daily data from meteorological stations to tourists' registration information. This approach allows for an understanding of travel volumes based on actual travel data and not on perceptions or desired outcomes. The results suggest a clear impact of weather on the number and duration of short-term trips for all seasons. There was no clear indication that weather forecasts played a significant role in the structure of mid or long term trips.
Isolation of Mercury-Resistant Endophytic and Rhizosphere Microorganisms from Grasses in Abandoned Gold Mining Area

There were about 900 hotspots of artisanal and small scale gold mining (ASGM) in Indonesia that recovered gold through amalgamation and cyanidation techniques. Amalgamation technique causes mercury (Hg) pollution to the soil. This study was a preliminary study that aimed to isolate Hg-resistant endophytic and rhizosphere microorganisms from pioneer grasses in the Hg-polluted soil. The most potential microorganism will be used for Hg phytoremediation in the future study. Pioneer grasses were collected from the abandoned gold mining area in Central Lombok Regency, West Nusa Tenggara. Total microorganisms were counted using Colony Forming Unit (CFU) or Standard Plate Count. The microorganism colony was characterized based on morphological characteristics. Hg-resistant endophytic and rhizosphere microorganisms were successfully isolated from pioneer grass (Cynodon dactylon and Eleusine indica) in the study site. The colonies of rhizosphere microorganisms were diverse morphologically compared to endophytic microorganisms based on the number of isolated microorganisms, 20 isolates and 17 isolates, respectively. The density of rhizosphere microorganisms was higher (96%) than endophytic microorganisms (4%). The density of rhizosphere bacteria and fungi were 47x103 and 2x103 CFU g-1, respectively. However, the density of endophytic bacteria and fungi were only 2x103 and 1x103 CFU g-1, respectively. Keywords: endophytic microorganism, Hg-resistant, microorganism density, rhizosphere microorganism
Shipping Bunker Cost Risk Assessment and Management during the Coronavirus Oil Shock

This research explores ways to develop a risk management strategy that enables shipping companies to reduce unnecessary fuel cost risks, fuel price fluctuations and improve financial management. Through the Monte Carlo method, the study makes use of the simulation of the conditional value-at-risk (CVaR) model. First, the VaR of various shipping-fuel-cost combination over a ten-year period is simulated. Then, through the most appropriate probability distribution test, it is found that most of the VaR of shipping fuel cost combination are in Beta–Arcsine distribution. In other words, the high-frequency data are concentrated at both tails (minimum and maximum) with high volatility. Therefore, the best strategy is to install scrubbers on existing ships to purify their exhaust gas and choose natural gas-based marine fuel for new ships. This will benefit the shipping companies significantly more compared to the use of low-sulfur fuel and choosing forward bunker agreements. Bunker swaps and options of bunker prices to hedging the risk of bunker cost raised in the end of Coronavirus oil shock, the strategy could help achieve the goal of risk management in the sustainable supply chain.