Miracle-dz/UniFAR-FTUs huggingface dataset:
Using UAV-based temporal spectral indices to dissect changes in the stay green trait in wheat

Stay green (SG) in wheat, a beneficial trait for increasing yield and stress resistance, needs to be supported by analysis of the underlying genetic basis. Spectral reflectance indices (SIs) provide non-destructive tools to evaluate crop temporal senescence. However, few SI-based SG quantification pipelines for analyzing diverse wheat panels in the field are available. Here, we first applied SIs to monitor the senescence dynamics of 565 diverse wheat accessions from anthesis to maturation stages during two field seasons. Based on over 12,000 SIs data set, four SIs (NDVI, GNDVI, NDRE and OSAVI) were selected to develop relative stay green scores (RSGS) and the senescence of wheat populations occurs mainly at four developmental stages stage 1 (S1) to S4, accounting for the final SG indicators. A RSGS-based genome-wide association study identified 47 high-confidence quantitative trait loci (QTL) harboring 3,079 SNPs significantly associated with RSGS and 1,085 corresponding candidate genes in the two seasons; 15 QTL overlapped or were adjacent to known SG-related QTL or genes and the remaining QTL were novel. Finally, we selected three superior candidate genes (TraesCS6B03G0356400, TraesCS2B03G1299500, and TraesCS2A03G1081100) as examples by transcriptomes, gene annotation, and gene-based association analysis for further analysis and found that utilization of superior SG-related variation in China gradually increased following the Green Revolution. The study provides a useful reference for further SG-related gene discovery of favorable variations in diverse wheat panels.
Numerical examination of niche effect on sound transmission loss of glass panes

: In the laboratory measurement of the sound transmission loss of platelike building elements, a specimen mounted between coupled rooms causes the so-called niche eﬀect. Normally a specimen is mounted inside an aperture in a thick wall, whereas in a special case where a specimen is mounted ﬂush with the wall, a projecting box frame is additionally installed outside the opening. Firstly, the measurements of a glass pane with the two types of niche are numerically modeled by vibro-acoustic simulation, and the niche eﬀect is examined while changing the niche depth and specimen position. As a result, it is revealed that the eﬀect of the projecting niche is generally smaller than that of the recessing niche. Secondly, regarding the cross-sectional shape of the recessing niche, the smaller eﬀect of the staggered niche speciﬁed in ISO 10140 is validated by comparison with that of a ﬂat niche. Additionally, the incidence angle dependence of the niche eﬀect is clariﬁed.
Formal Expressions Which Can be Applied to Cusum Charts

The paper describes a number of formal expressions which can be used to determine properties of cumulative sum schemes. Formulae given only depend upon very general assumptions with regard to the distribution of the cumulated statistic. Numerical as well as algebraic procedures are described which permit calculation of the average sample run length to a specified degree of accuracy for almost any statistic likely to arise in practice. Methods for generating the sample run length distribution are also given.
Particle resuspension by a periodically forced impinging jet

When hovering over sandy terrain, the rotor of helicopters generates a downward jet that induces resuspension of dust and debris. We investigate the mechanisms that govern particle resuspension in such flow using an Eulerian–Lagrangian approach based on large-eddy simulation of turbulence. The wake generated by the helicopter is modelled as a vertical impinging jet, to which a sequence of periodically forced azimuthal vortices is superposed. The resulting flow field provides a unique range of flow scales with which the particles can interact. Downstream of the impingement region, layers of negative azimuthal vorticity (secondary vortices) form on the upwash side of the primary azimuthal (large-scale) vortices. These layers then detach from the surface together with the near-wall (small-scale) vortices populating the wall-jet region. We show how the dynamics of sediments is governed by its interaction with these structures. After initial lift off from the impingement surface, particles accumulate in regions where near-wall vortices roll around the impinging azimuthal vortex, forming rib-like structures that either propel particles away from the azimuthal vortex or entrap them in the shear layer between the azimuthal and secondary vortices. We demonstrate that these trapped particles are more likely to reach the outer flow region and generate a persistent cloud of airborne particles. We also show that, in a time-averaged sense, particle resuspension and deposition fluxes balance each other near the impingement surface.
A Delimitation of Data Sovereignty from Digital and Technological Sovereignty

Digital technology significantly impacts our everyday social lives and how we conduct business. This development results in abundant new data generated by people and organizations. Subsequently, future technological instruments must ensure data sovereignty that empowers individuals to maintain control over their data. However, data sovereignty is still blurry and conceptually overlaps with similar terminologies, such as digital and technological sovereignty. From an Information Systems (IS) point of view, delimiting data sovereignty from digital and technological sovereignty is crucial, creating a uniform understanding, especially for data ecosystems. Our study contributes to sharpening data sovereignty with a systematic literature review of 81 articles. It concludes that data sovereignty mainly drives IS activities by protecting data assets on individual and organizational levels. In contrast, digital sovereignty is shaped by digital expertise and interoperability, while technological sovereignty is the broadest concept with regulations and relations on an international level.
A New One/Two-Dimensional Model of the Conjugate Heat Transfer in Waterwall Tubes of the Supercritical Steam Boiler Combustion Chamber

ABSTRACT An important issue arising in supercritical steam boilers is to avoid the tube wall overheating due to high heat fluxes transferred from flue gases to the fluid. The paper presents a new hybrid one/two-dimensional model of the fluid heating in waterwall tubes in the combustion chambers of steam boilers for supercritical steam parameters. The model is based on distributed parameters. The analysis concerns tubes with externally finned surfaces. Using the proposed model, it is possible to estimate zones and locations where the tube wall overheating may occur. One-dimensional equations describing the mass, momentum and energy conservation are formulated and solved for the fluid domain. Each analyzed cross section of the finned waterwall tube is divided into 20 control volumes for which energy balance equations are solved in a two-dimensional space. In order to analyses the conjugate heat transfer between the waterwall tube and the fluid, the heat transfer coefficient is computed using the Kitoh correlation. The computations assume a variable heat flux along the combustion chamber height. Also, the heat flux variation on the waterwall tube circumference is incorporated within the model. The reduction in dimensionality in both the fluid and the solid domains leads to an improvement in the computational performance compared to complex three-dimensional computational fluid dynamics simulations. The paper presents an application of the proposed hybrid model to simulate heat and flow processes occurring in waterwall tubes of a supercritical boiler operating in one of the Polish power plants. The results of the simulations are compared with the data obtained from measurements and good agreement is obtained. Therefore, the developed model can be successfully applied, e.g. in simulators of the supercritical power boiler operation.
A Socio-Ecological-Technical Perspective: How has Information Systems Contributed to Solving the Sustainability Problem

This literature review extends the dominant view of Information Systems (IS) as socio-technical. We establish a novel view of IS as socio-ecological-technical systems to steer and unite IS research and scholarship to co-create digitally transformed sustainable futures. Without a commitment to reducing carbon dioxide equivalent emissions (CO 2 e), we will reach a tipping point leading to large-scale, dangerous, and irreversible impacts on climate, human liveability, and survivability. Digital technology can potentially mediate human activities to reduce CO 2 e, but its production, utilisation, and disposal are multiple sources of CO 2 e. In response to the conference theme “Co-creating Sustainable Digital Futures”, this paper systematically reviews the IS research over the last twelve years from the socio-ecological-technical and Environmentally Sustainable Digital Transformation frameworks, with a focus on CO 2 e. Our holistic approach reveals emerging themes, current gaps and research opportunities, thus contributing to IS knowledge building and proposing future studies in this socio-ecological-technical domain.
On helical springs of finite thickness

where b is a positive constant to be determined. Then the graph of P{x) is a polygonal path with vertices having abscissas on 0 g x < L at x = 0, d, • • • , (2n — 1 )d. It will be shown that for a proper choice of the constant b the function P(x) of (1) has maxima occurring at the points x = 0, 2d, ■ • • , (2n — 2)d. For reasons of continuity, it is clear that the above p(x) can be replaced by a continuous positive function possessing a single maximum on the interval 0 ^ x ^ L and so that the corresponding P(x) of (1) possesses n maxima on 0 ^ x < L; see the remark of [1], p. 272. An easy calculation shows that, for the p(x) of (2), the function P(x) satisfies
Introducing Variability Promotes Motor and Language Learning

We inquired whether introducing variability into a word-learning task would facilitate, inhibit, or have a neutral effect on adults’ speech production and language learning. Twenty young adults from the U.S. Midwest with typical development participated. They repeated four novel words 10 times sequentially (blocked practice) and another four novel words 10 times in a mixed order (varied practice). We compared participants’ speech production and language learning in the blocked practice and varied practice conditions. We also repeated the language-learning probes after a period of consolidation. In comparison with the blocked practice condition, a varied practice schedule did not improve speech production, shortterm language learning, or long-term language learning. Introducing variability into this word-learning task had a neutral effect on young adults’ speech production and language learning. Further research is necessary to determine how to apply these concepts to teaching word-learning strategies to children or adults with typical or atypical development.
A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting the current aviation spectrum to accommodate future air operations. To tackle this challenge, the concept of intelligent spectrum management is proposed for autonomous and dynamic resource allocations, where accurate aircraft position estimation is one of the crucial tasks. However, current research on flight trajectory prediction has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. In this paper, we propose a generalized hybrid-recurrent predictive model for flight trajectory prediction. Our generalizable deep learning approach not only improves trajectory prediction accuracy, but also can be contextualized by exploring a large amount of data. Experimental results illustrate a tradeoff between horizontal and vertical errors as flight data are generalized across dates and routes.
DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics

In this work, we aim to learn dexterous manipulation of deformable objects using multi-fingered hands. Reinforcement learning approaches for dexterous rigid object manipulation would struggle in this setting due to the complexity of physics interaction with deformable objects. At the same time, previous trajectory optimization approaches with differentiable physics for deformable manipulation would suffer from local optima caused by the explosion of contact modes from hand-object interactions. To address these challenges, we propose DexDeform, a principled framework that abstracts dexterous manipulation skills from human demonstration and refines the learned skills with differentiable physics. Concretely, we first collect a small set of human demonstrations using teleoperation. And we then train a skill model using demonstrations for planning over action abstractions in imagination. To explore the goal space, we further apply augmentations to the existing deformable shapes in demonstrations and use a gradient optimizer to refine the actions planned by the skill model. Finally, we adopt the refined trajectories as new demonstrations for finetuning the skill model. To evaluate the effectiveness of our approach, we introduce a suite of six challenging dexterous deformable object manipulation tasks. Compared with baselines, DexDeform is able to better explore and generalize across novel goals unseen in the initial human demonstrations.
Analysis of the fragmentation function based on ATLAS data on proton-proton collisions at √s=7 TeV

In high energy particle physics, the collision of two protons leads to quantum interactions through the strong force. This interactions produce highly energetic scattered particles that start to produce more particles forming collimated cones of particles, called jets. The phenomena that produces these jets from the scattered particles is called hadronization, and is explained using the fragmentation function. In this work, the fragmentation functions from with the PYTHIA Monte Carlo event generator and the data from the ATLAS experiment in various jet energy ranges and they were used to study a cascade model proposed by Richard Feymann and Richard Field. I found that PYTHIA is able to reproduce the ATLAS data with reasonable precision. The model results are presented using two different kinds of data: one being the same as used by ATLAS, and another with higher granularity data. The Feynman model is able to describe the data within ranges of 20% for most of the jet energy ranges available. It is remarkable how the results obtained by applying the model to the ATLAS data agree with the results of the model with the PYTHIA simulation.
Evidence for two distinct defect related luminescence features in monolayer MoS2

Apart from the defect related emission peak which lies ∼100 meV below the A exciton/trion peak and is labeled D1 here, this study shows that there is another distinct feature D2 lying ∼200 meV below A in the photoluminescence spectrum of the exfoliated monolayer MoS2 on SiO2/Si substrates. The D2 feature is explicitly resolved at low temperature only in few samples. Both D1 and D2 do not show circular polarization anisotropy for 633 nm excitation. Both decay with the increase in temperature in a seemingly activated manner with similar activation energy of ∼50 meV, but D1 decays earlier and therefore D2 dominates at high temperature in all samples. Annealing in vacuum increases both D1 and D2 emission intensities while annealing under sulfur vapour decreases them. Comparison with reported theoretical studies on defects in monolayer MoS2 suggests that these two emissions possibly involve excitons bound to single and double sulphur vacancies, the latter binding excitons more strongly.
On the acoustic radiation from boundary layers and jets

In the following a general discussion of aerodynamically created sound is given. The study is essentially theoretical in nature, but arrives at a description of the physical phenomena in such a fashion as to yield an immediate access to experiments. First, the problem of aerodynamic noise is defined and two simple mechanical analogues discussed. Then, the general equations of motion of a viscous, compressible fluid are rearranged in a form suitable for a comparison with Lighthill's approach. However, this approach is not being followed through. Instead, the concept of induced velocities due to displacement effects is put forward and carried through for noise produced by boundary layer flow. The same concept is then extended to describe the sound field created by a jet.
Consequences of Green Transformational Leadership: Insights on Resort Employees at Marsa Alam

This paper highlights consequences of green transformational leadership (GTL) at Egyptian resorts through organizational citizenship behavior for the environment (OCBE). We received 338 responses from deluxe resort employees located in Marsa Alam. The findings revealed that employees showed high levels of motivation when their supervisors exhibited transformational leadership behaviors. Moreover, a higher level of sustainability for resort employees was achieved as a consequence of their involvement in environmentally friendly activities, such as employee green creativity. These findings offer valuable insights into the potential of green leadership to enhance resort sustainability.
Event Vision in Egocentric Human Action Recognition

This paper lies at the intersection of three research areas: human action recognition, egocentric vision, and visual event-based sensors. The main goal is the comparison of egocentric action recognition performance under either of two visual sources: conventional images, or event-based visual data. In this work, the events, as triggered by asynchronous event sensors or their simulation, are spatio-temporally aggregated into event frames (a grid-like representation). This allows to use exactly the same neural model for both visual sources, thus easing a fair comparison. Speci(cid:28)cally, a hybrid neural architecture combining a convolutional neural network and a recurrent network is used. It is empirically found that this general architecture works for both, conventional gray-level frames, and event frames. This (cid:28)nding is relevant because it reveals that no modi(cid:28)cation or adaptation is strictly required to deal with event data for egocentric action classi(cid:28)cation. Interestingly, action recognition is found to perform better with event frames, suggesting that these data provide discriminative information that aids the neural model to learn good features.
Journal of International Women's Studies Journal of International Women's Studies

Saudi Vision 2030 was launched with a focus on three main themes: “a vibrant society,” “a thriving economy,” and “an ambitious nation” (2017). In order to realize these primary themes, more participation of women is required in the workforce. A number of legislative reforms have supported the entry of more women into the workforce, such as lifting the male guardian permission for work and travel, supporting programs for childcare, allowing women to drive cars, and ensuring women’s involvement in leadership positions. Saudi women are now working in defense, mining, construction, manufacturing, and retail among other sectors. As a result, women's participation in the workforce increased from 19.4% in 2017 to 35.6% in the second quarter of 2022. Because these social and economic transformations have the potential to influence the dynamics within the Saudi family, this study investigates the attitudes of Saudi men and women toward gender roles within the Saudi family. Based on the short version of the Attitudes toward Women Scale, an online questionnaire was sent to a random sample of 431 Saudis in the fall of 2022. Statistical analyses were conducted to measure women’s attitudes compared to men’s overall scores. Results of the independent sample t -test indicated that women held more pro-feminist attitudes compared to men.
Studying Maladaptive Daydreaming’s Impact on Impulsivity

Maladaptive daydreaming usually involves compulsive and obsessive daydreaming where fantasies can be complex and be resumed and paused at any time. The studies have not used, as far as to this researcher’s knowledge, cognitive behavioral tasks to measure MD. This study uses the maladaptive daydreaming scale – 16 (Somer, Soffer-Dudek, Ross, et al., 2017) (MDS-16) and the immediate and delayed memory tasks (Dougherty et al., 2002) (IMT/DMT) to measure the maladaptive daydreamer’s impulsiveness. Although there were 157 that began the task, only 13 completed the entire experiment, with only one participant completing one block. Although the participant pool is small, data analysis has shown that those with a high MDS-16 score show high impulsivity; however, there were no participants that scored below a 50 on the MDS-16 scale, so no comparison could be made between a MD group and a non-MD group.
N O C HILD IS L EFT B EHIND ? ——E DUCATION P ROBLEMS OF L EFT -B EHIND C HILDREN IN C HINA

Urbanization in developing countries has raised concerns about the education of left-behind children. Using the fixed effect model and the time-varying difference-in-difference model, we examine how left-behind experiences affect children’s educational choices and identities. We find that left-behind children have an approximately 2% higher probability to drop out of school. They tend to report lower levels of education expectations and education expenditures. The negative effect of left-behind experiences on education outcomes is significant, particularly among middle-school students. Despite improved living conditions, these findings suggest that left-behind experiences have hindered many children from enjoying educational success.
Parents and Teachers’ Perceptions of Online Music Sessions for Children with Autism During the Covid-19 Pandemic in Malaysia: An Exploratory Feasibility Study

Autism is a neurological disorder that manifests as social communication skill limitations, fixated interests and rigid behaviours. During the COVID-19 pandemic in Malaysia, online lessons became the norm and it transformed the way teachers and parents collaborated to ensure that children with autism continued to receive education from home. However, parents of autistic children noticed a marked regression in basic living skills and communication skills in their children during the pandemic. The importance of music has been indicated by a growing body of research as it can help children with autism maintain and develop social and communication skill. While research during the pandemic revealed that children with autism’s age, cognitive functioning, family income, parent education and cultural background are factors that may influence treatment selection and outcomes, parents and teachers’ positive and negative perceptions of online learning experiences with the child may also contribute to it. The purpose of this exploratory study was to gauge the perceptions of parents and teachers towards online education in order to determine the feasibility of introducing music therapy-based online music classes for children with autism as a potential means to promote and preserve their social and communication skills. A total of 59 teachers and 69 parents participated in this study by answering a prepared online survey questionnaire through Google Docs. The findings were analysed using conventional content analysis and later with descriptive statistic on SPSS. The findings from this study indicated that parents are more interested in having online music sessions with their children compared to teachers. Teachers are less interested due to the lack of musical skill to deliver quality online sessions with music. Based on parents and teachers ’ overall perceptions, this study found that children with autism had the potential to benefit from online music lessons aimed at stimulating social and communication skills