Miracle-dz/UniFAR-FTUs huggingface dataset:
A Variable Attention Nested UNet++ Network-Based NDT X-ray Image Defect Segmentation Method

In this paper, we describe a new method for non-destructive testing (NDT) X-ray image defect segmentation by introducing a variable attention nested UNet++ network. To further enhance the performance of the faint defect extraction and its clear visibility, a pre-processing method based on pyramid model is also added to the proposed method to effectively perform high dynamic range compression and defect enhancement on the 16-bit raw image. To illustrate its effectiveness and efficiency, we applied the proposed algorithm to the X-ray image defect segmentation problem and carried out extensive experiments. The results support that the proposed method outperforms the existing representative techniques in extracting defect for real X-ray images collected directly from industrial lines, which achieves the better performance with 89.24% IoU, and 94.31% Dice.
Understanding Academic Fraud: The Role of Dark Triad Personality and Situational Factor

Abstract Academic fraud is a perennial problem, and the Covid-19 pandemic has exacerbated it with most universities moving to online learning. We conducted a survey with 259 students from three universities about their perceptions of academic fraud in online learning. This article examines whether individual factors drawing from the dark triad of personality and three situational factors: academic integrity culture, academic fraud ambiguity, and pressure, influence the intention to engage in academic fraud. Using partial least square-structural equation modeling, the results show that academic integrity culture, pressure, and the dark triad of personality significantly affect students’ intention to engage in academic fraud. The implication of such findings is discussed.
Genome-Wide Identification of Rapid Alkalinization Factor Family in Brassica napus and Functional Analysis of BnRALF10 in Immunity to Sclerotinia sclerotiorum

Rapid alkalinization factors (RALFs) were recently reported to be important players in plant immunity. Nevertheless, the signaling underlying RALF-triggered immunity in crop species against necrotrophic pathogens remains largely unknown. In this study, RALF family in the important oil crop oilseed rape (Brassica napus) was identified and functions of BnRALF10 in immunity against the devastating necrotrophic pathogen Sclerotinia sclerotiorum as well as the signaling underlying this immunity were revealed. The oilseed rape genome carried 61 RALFs, half of them were atypical, containing a less conserved YISY motif and lacking a RRXL motif or a pair of cysteines. Family-wide gene expression analyses demonstrated that patterns of expression in response to S. sclerotiorum infection and DAMP and PAMP treatments were generally RALF- and stimulus-specific. Most significantly responsive BnRALF genes were expressionally up-regulated by S. sclerotiorum, while in contrast, more BnRALF genes were down-regulated by BnPep5 and SsNLP1. These results indicate that members of BnRALF family are likely differentially involved in plant immunity. Functional analyses revealed that BnRALF10 provoked diverse immune responses in oilseed rape and stimulated resistance to S. sclerotiorum. These data support BnRALF10 to function as a DAMP to play a positive role in plant immunity. BnRALF10 interacted with BnFER. Silencing of BnFER decreased BnRALF10-induced reactive oxygen species (ROS) production and compromised rape resistance to S. sclerotiorum. These results back BnFER to be a receptor of BnRALF10. Furthermore, quantitative proteomic analysis identified dozens of BnRALF10-elicited defense (RED) proteins, which respond to BnRALF10 in protein abundance and play a role in defense. Our results revealed that BnRALF10 modulated the abundance of RED proteins to fine tune plant immunity. Collectively, our results provided some insights into the functions of oilseed rape RALFs and the signaling underlying BnRALF-triggered immunity.
A New Look at the Coding in Time-Modulated Arrays

— In this paper, we show that the digital code bits used in the coded time-modulated arrays (TMA) can be interpreted as vector elements, and with this new interpretation, a better understanding of the relationship between the codes and the amplitude/phase of the generated harmonic signals is obtained. Using such interpretation, we first select the proper codes for the maximum radiation in a coded TMA, and then we show that one can easily perform the beam steering in a TMA by electronically shifting the bits of the selected codes. Through full-wave simulations, we demonstrate the beam steering of a TMA without the use of any phase shifter, and only by shifting the digital code bits. The proposed interpretation can play an important role in reducing the complexity of the code selection in controlling of TMAs.
Learning to Use Office Applications: Understanding the Antecedents of Adaptive IT Use

Surprisingly, in addition to inexperienced computer users, also those who have used different software applications at least to moderate extent can have feelings of anxiety with their use of computers. This paper examines the role of training in decreasing anxiety among experienced computer users. More specifically, the role of training is studied in relation to computer anxiety, behavioral beliefs and selfefficacy, which are the key mental constructs training may impact. 96 adult and university students, who attended a CDL course on voluntary basis, participated in this longitudinal study. The results suggest that training is an effective tool to decrease anxiety and promote self-efficacy even among experienced users. In addition this study calls in the question of the relation of computer anxiety and ease of use.
Measuring the refractive index and sub-nanometre surface functionalisation of nanoparticles in suspension

Direct measurements to determine the degree of surface coverage of nanoparticles by functional moieties are rare, with current strategies requiring a high level of expertise and expensive equipment. Here, a practical method to determine the ratio of the volume of the functionalisation layer to the particle volume based on measuring the refractive index of nanoparticles in suspension is proposed. As a proof of concept, this technique is applied to poly(methyl methacrylate) (PMMA) nanoparticles and semicrystalline carbon dots functionalised with different surface moieties, yielding refractive indices that are commensurate to those from previous literature and Mie theory. In doing so, it is demonstrated that this technique is able to optically detect differences in surface functionalisation or composition of nanometre-sized particles. This non-destructive and rapid method is well-suited for in situ industrial particle characterisation and biological applications.
Polychronicity, decision-making and entrepreneurial self-efficacy of venture team founders: an exploratory study

PurposeThis study explores the role of polychronic temporal orientation and decision-making decentralization on founders' perceptions of entrepreneurial self-efficacy (ESE). Design/methodology/approachLongitudinal survey data were collected from 141 business founders in China.FindingsFindings suggest that decision-making decentralization is positively associated with founders' ESE. In addition, a polychronic temporal orientation is positively related to ESE, and this relationship is mediated by decision-making decentralization.Originality/valueThis study adds to existing knowledge on ESE and temporal related issues by presenting empirical evidence that explains how and why the temporal orientation context and the practice of decision-making decentralization can shape ESE perceptions among venture founders.
Automatic extraction method of damage point of laser weapon

In the face of increasingly severe air target threats, laser weapons have the advantages of fast attack speed, flexible steering, precision strikes and immunity from electromagnetic interference. They are new concept weapons that are developed by the navies of various countries. At present, laser weapons strike targets, relying on manual point selection to directional strike damage points, which takes a long time, and it is easy to miss the time of damage. In order to solve the timeconsuming problem of manual point selection, this paper proposes an automatic extraction method for damage points of laser weapons. This method divides the missile target by K_means color clustering, and then fits the center line of the missile according to the pixel position index of the missile target area, combined with the least square method, and finally extracts the damage point according to the proportion of each part in the missile. This method can accurately provide damage points in real time and improve the combat effectiveness of laser weapons
Establishing Transparency for Distribution Grid Planning and Operation Using Methods of State Estimation

The integration of distributed energy resources in distribution grids leads to new challenges for planning and operation as uncertainty about the grid state is increased concurrently. State estimation can identify the grid state in distribution grids with little measurements in place. In this paper a low voltage grid in Germany was analysed. It was found that the estimates of the grid states in a high temporal resolution are of suitable accuracy and can be used for deriving relevant cases to be considered in grid planning. The three-phase implementation allows the analysis of both the voltage magnitude and the differences in phase voltages.
A Biomimetic Vision Architecture

The goal of biomimetic vision is to build artificial vision systems that are analogous to the human visual system. This paper presents a software architecture for biomimetic vision in which every major component is clearly defined in terms of its function and interface, and where every component has a analog in the regional functional anatomy of the human brain. We also present an end-to-end vision system implemented within this framework that learns to recognize objects without human supervision.
Business analysis and modelling of flight delays using artificial intelligence

In the current day, with the growth of technology the number of people travelling by flights has increased. Consistently a significant number of flights are delayed or crossed out because of numerous of reasons. These delays bother travelers. These delays also cost a lot to the aircraft organization. Flight delays negatively affect carriers, air terminals and travelers. There are different methodologies used to manufacture flight delays expectation models from the Data Science point of view. The key resource of a flight includes aircraft, cockpit crew and cabin crew. For purposes of dispatching resources effectively, the three resources may be distributed independently. If the initial flight of a flight plan is delayed due to bad weather or other factors, it may result in the delays of the directly downstream flights that need to await its resources. If the delays continue to spread to the lower downstream flights, it may result in large area delay propagation. The method proposed here introduces and summarizes the initiatives used to address the flight delay prediction problem, according to scope, data and computational methods, giving special attention to an increasing usage of machine learning methods.
Pareto Multiobjective Lyapunov-Based Economic Model-Predictive Control for Nonlinear Time-Delayed System

This article proposes a dual-mode multiobjective Lyapunov-based economic model-predictive control (MOLEMPC) for constrained nonlinear time-delay systems with external disturbances. First, considering the conflicting objectives, the Pareto compromise approach is used to calculate the compromised economic stability point and the multiobjective optimization function. To compensate for the impact of input delay, a model-based estimator is designed by using the actual state, historical inputs, and nominal models of the system. By the proposed dual-mode Lyapunov-based economic model-predictive control (LEMPC) scheme, the feasible domain of the initial point of a closed-loop system is increased, in the meantime, the stability of the closed-loop system with disturbances and delay is guaranteed. The recursive feasibility and stability analysis of the MOLEMPC controller is given in detail. We illustrate that the closed-loop system state converges in a robust invariant set after a finite time. Finally, simulations demonstrate the reliability and advantages of the proposed strategy.
Whole-stand growth and yield models for Pinus patula

Predicting the growth and yield of timber tree species is a prerequisite for planning sustainable forest management. The objective was to update several functions that integrate a compatible growth and yield system for Pinus patula, developed under the explicit wholestand model approach. System parameters were estimated using seemingly unrelated regression. For that, forest biometric information was used from four periodical inventories conducted in 42 permanent plots of 400 m 2 in Hidalgo, Mexico. Almost all the functions of the system had good fit and satisfactory graphical behavior in their original structure. A polymorphic growth pattern explains stand productivity, which is interrelated with growth equations of basal area, mean diameter and total stem volume per hectare. The mortality function corresponds to an exponential model fitted under non-linear least squares method. The re-fitted system broadened the range of the growth equations to 31 years. The new system suggests a maximizing volume rotation of about 20 years for the average site. These results suggest that the commonly used 40 year rotation period used in the management plans in the region could be shortened if a proper density management strategy is applied.
How Is the Ocean Anthropogenic Carbon Reservoir Filled?

About a quarter of the total anthropogenic CO2 emissions during the industrial era has been absorbed by the ocean. The rate limiting step for this uptake is the transport of the anthropogenic carbon (Cant) from the ocean mixed layer where it is absorbed to the interior ocean where it is stored. While it is generally known that deep water formation sites are important for vertical carbon transport, the exact magnitude of the fluxes across the base of the mixed layer in different regions is uncertain. Here, we determine where, when, and how much Cant has been injected across the mixed‐layer base and into the interior ocean since the start of the industrialized era. We do this by combining a transport matrix derived from observations with a time‐evolving boundary condition obtained from already published estimates of ocean Cant. Our results show that most of the Cant stored below the mixed layer are injected in the subtropics (40.1%) and the Southern Ocean (36.0%), while the Subpolar North Atlantic has the largest fluxes. The Subpolar North Atlantic is also the most important region for injecting Cant into the deep ocean with 81.6% of the Cant reaching depths greater than 1,000 m. The subtropics, on the other hand, have been the most efficient in transporting Cant across the mixed‐layer base per volume of water ventilated. This study shows how the oceanic Cant uptake relies on vertical transports in a few oceanic regions and sheds light on the pathways that fill the ocean Cant reservoir.
Numerical Study of Aerodynamic Characteristics of a Symmetric NACA Section with Simulated Ice Shapes

To develop a numerical model of icing on wind turbine blades, a CFD simulation was conducted to investigate the effect of critical ice accretions on the aerodynamic characteristics of a 0.610 m chord NACA 0011 airfoil section. Aerodynamic performance coefficients and pressure profile were calculated and compared with the available measurements for a chord Reynolds number of 1.83x106. Ice shapes were simulated with flat plates (spoiler-ice) extending along the span of the wing. Lift, drag, and pressure coefficients were calculated in zero angle of attack through the steady state and transient simulations. Different approaches of numerical studies have been applied to investigate the icing conditions on the blades. The simulated separated flow over the sharp spoilers is challenging and can be seen as a worst test case for validation. It allows determining a reliable strategy to simulate real ice shapes [1] for which the detailed validation cannot easily be provided.
Black Lives Matter: The Role of Emotions in Political Engagement

In the spring of 2020, the Black Lives Matter protests shook the Western world. Spreading from the USA, demonstrations diffused globally, especially to Europe, calling out racism in its different forms. Emotions ran high and were pivotal in igniting protests. The role of emotion in social movements has received renewed scholarly attention during the last decades. It plays an important role at every stage of protest, but few studies have traced its part in individuals’ shifting engagement over time. This study examines the role of emotion during the global wave of Black Lives Matter protests. Based on retrospective interviews with 38 participants in Black Lives Matter demonstrations in Norway, we identify the role of emotion before, during and after their participation. Our findings help explain how individual patterns of participation develop in the course of a wave of protest, and also provide insights into the consequences of the recent Black Lives Matter protests in Europe.
Co-designing alternative frames of ageing and experiences of challenging ageism in Australia

ABSTRACT Ageism is an ongoing pervasive issue that can be difficult to challenge. The aims of this study were to co-design alternative frames about aging in a workshop and to explore the process participants went through using these to challenge ageism in their communities over a three-month period. Participatory action research combined with co-design were used. Full-day workshops involving 27 participants across urban and regional Australia introduced participants to the concept of ageism, framing, engaging with community, and co-designing alternative frames of aging. An online group allowed participants to support each other and continue exploring ideas as they challenged ageism in their communities. After 3 months, follow-up debrief sessions involving activities and semi-structured interviews were conducted. Data from workshops (activities, recordings), online posts, and debrief sessions were analyzed. Participants found the reframing process useful for challenging aging stereotypes in the community. Over the three months they developed an increased awareness of ageism (in self, others, society) and challenged these in different ways, including changing their internal dialogue, challenging others’ views on aging, and actively defying stereotypes. Five alternative frames emerged: diversity and human rights; empowerment and support; value/contributions; lifelong learning; intergenerational. The process of creating alternative frames was important and allowed participants to bring their own values andnarratives to the experience.
Istraživanje otpora potopljenog dijela jedrilice klase Optimist.

U ovom radu su istražene promjene hidrodinamickog otpora i momenta zakreta uronjenog dijela trupa jedrilice klase ’Optimist”. Promatrana je ovisnost hidrodinamickih sila o dva parametra: kutu zakreta kormila i kutu bocnog nagiba jedrilice. Trodimenzionalna geometrija je modelirana u programskom paketu Solidworks, dok je proracunska domena izrađena u programskom paketu Salome. Istisnina jedrilice je automatski generirana koristeci prethodno navedene programske pakete i to za masu jedrilice od 35kg te srednju masu jedrilicara od 45kg. Domena je ispunjena mrežom konacnih volumena koristeci programski paket cfMesh. Mreža je izrađena strukturirano koristeci heksaedarske celije, uz koristenje manjeg broja prijelaznih tetraedarskih i piramidalnih celija kao i trokutnih prizmi kako bi se ocuvala geometrijska definicija rubova. Ulazni parametri strujanja su definirani uniformno, prema zadanoj brzini jedrilice od 1.5m/s tj. 3 cvora. Simulacije su izvedene stacionarnim proracunom, koristeci k − ω SST model turbulencije i standardne zidne funkcije. Kako bi se pojednostavnio proracun i skratilo vrijeme racunanja, zanemaren je utjecaj valova te je rubni uvjet simetrije definiran na mjestu slobodne povrsine. Izrađene su simulacije za sest konfiguracija položaja kormila, dva položaja bocnog nagiba te cetiri kombinacije bocnog nagiba i zakreta kormila. Prikazana su polja raspodjele transportiranih fizikalnih velicina kako bi se dobio uvid u procese strujanja u okolici uronjenog dijela trupa. Analizom rezultata su utvrđeni doprinosi viskoznih i tlacnih hidrodinamickih sila sveukupnom otporu. Također prikazane su krivulje promjene hidrodinamickih momenta zakreta s promjenom navedenih parametara. Konacno, dan je zakljucak o kvaliteti pojedine konfiguracije na temelju dobivenih proracunskih podataka.
Adaptive Gaussian filters for nonlinear state estimation with one‐step randomly delayed measurements

This paper proposes new algorithms of adaptive Gaussian filters for nonlinear state estimation with maximum one‐step randomly delayed measurements. The unknown random delay is modeled as a Bernoulli random variable with the latency probability known a priori. However, a contingent situation has been considered in this work when the measurement noise statistics remain partially unknown. Due to unavailability of the complete knowledge of measurement noise statistics, the unknown measurement noise covariance matrix is estimated along with states following: (i) variational Bayesian approach, (ii) maximum likelihood estimation. The adaptation algorithms are mathematically derived following both of the above approaches. Subsequently, a general framework for adaptive Gaussian filter is presented with which variants of adaptive nonlinear filters can be formulated using different rules of numerical approximation for Gaussian integrals. This paper presents a few of such filters, viz., adaptive cubature Kalman filter, adaptive cubature quadrature Kalman filter with their higher degree variants, adaptive unscented Kalman filter, and adaptive Gauss–Hermite filter, and demonstrates the comparative performance analysis with the help of a nontrivial Bearing only tracking problem in simulation. Additionally, the paper carries out relative performance comparison between maximum likelihood estimation and variational Bayesian approaches for adaptation using Monte Carlo simulation. The proposed algorithms are also validated with the help of an off‐line harmonics estimation problem with real data.