Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of What Others Do, Approve Of, and Expect You to Do: An In-Depth Analysis of Social Norms and Self-Disclosure on Social Media

There are many factors that account for disclosure of private information on social network sites, but a potentially powerful determinant that remains understudied is social norms, which refer to perceptions of what other people do, approve of, and expect us to do on social media. To address this gap, we conducted an in-depth analysis of descriptive, injunctive, and subjective norms for verbal and visual disclosure on Facebook and Instagram, using a preregistered survey study with 863 participants. We further analyzed whether critical media literacy and media-related self-reflection could buffer against uncritical adoption of these norms. The findings revealed that all three types of norms positively and independently predicted self-disclosure, regardless of the platform or type of self-disclosure (visual vs. verbal), while controlling for other common predictors of self-disclosure, including perceived benefits and risks of self-disclosure. Self-reflection and critical media literacy neither directly predicted disclosure, nor accounted for differences in norm-behavior relationships.
Course Scheduling Under Uncertainty for Defence Workforce Training

: In this paper, we revisit a previously studied Defence course scheduling problem where trainees are allocated to course sessions, the Simultaneous Sequencing and Allocation Problem. The courses have a non-linear prerequisite structure, each course has a number of sessions, and each session has a class size limit. The uncertainty in the planning is due to a historical pass-rate associated with each course, and a trainee will not be able to proceed once s/he fails a course. We develop a simulation-based three-stage solution algorithm that optimises the scheduling for each scenario using integer programming. The way pass-rates are handled is different from previous approaches, and because of this, we are able to provide decision-makers with better insights on best-case, average-case, and worst-case outcomes.
WSAM: Visual Explanations from Style Augmentation as Adversarial Attacker and Their Influence in Image Classification

Currently, style augmentation is capturing attention due to convolutional neural networks (CNN) being strongly biased toward recognizing textures rather than shapes. Most existing styling methods either perform a low-fidelity style transfer or a weak style representation in the embedding vector. This paper outlines a style augmentation algorithm using stochastic-based sampling with noise addition to improving randomization on a general linear transformation for style transfer. With our augmentation strategy, all models not only present incredible robustness against image stylizing but also outperform all previous methods and surpass the state-of-the-art performance for the STL-10 dataset. In addition, we present an analysis of the model interpretations under different style variations. At the same time, we compare comprehensive experiments demonstrating the performance when applied to deep neural architectures in training settings.
Neural Style Transfer for Image-Based Garment Interchange Through Multi-Person Human Views

: The generation of photorealistic images of human appearances under the guidance of body pose enables a wide range of applications, including virtual fitting and style synthesis. Several advances have been made in this direction using image-based deep learning generation approaches. The issue with these methods is that they produce significant aberrations in the final output, such as blurring of fine details and texture alterations. Our work falls within this objective by proposing a system able to realize the garment transfer between different views of person by overcoming these issues. To realize this objective, fundamental steps were achieved. Firstly, we used a conditioning adversarial network to deal with pose and appearance separately, create a human shape image with precise control over pose, and align target garment with appropriate body parts in the human image. As a second step, we introduced a neural approach for style transfer that can differentiate and merge content and style of editing images. We designed architecture with distinct levels to ensure the style transfer while preserving the quality of original texture in the generated results.
Prostate Cancer Detection, Segmentation, and Classification using Deep Neural Networks

: This paper provides a fully automated computer-aided medical diagnostic system that assists radiologists in segmenting Prostate Cancer (PCa) Lesions from multi-parametric Magnetic Resonance Imaging (mp-MRIs) and predicting whether those lesions are benign or malignant. For that, our proposed approach used deep learning neural networks models such as residual networks (ResNet) and inception networks to classify clinically relevant cancer. It also used U-Net and MultiResU-Net to automatically segment the prostate lesion from mp-MRI’s. We used two publicly available benchmark datasets: the Radboudumc and ProstateX. We tested our fully automatic system and obtained positive findings, with the AUROC of the PCa lesion classification model exceeding 98.4% accuracy. On the other hand, the MultiResU-Net model achieved an accuracy of 98.34% for PCa lesion segmentation.
Evaluation innovation in Africa: Towards indigenously responsive evaluation (IRE) philosophies, methods and practices in Ghana

Evaluation within an indigenous society is a social activity. Thus, it requires both tangible and intangible or hidden factors such as cultural values, norms, communal relational structures, power dynamics, attitudes, consensus-building, community aspirations, empowerment and other practical knowledge to develop an inclusive evaluation framework. Utilizing a culturally responsive evaluation (CRE) approach, this study examined evaluative instincts rooted in indigenous values, relational patterns, knowledge systems and other cultural realities. Indigenous evaluation impulse exists in native ideas, social structures and other cultural realities but could these indigenous evaluative impulses augment and shape contemporary evaluation philosophies, approaches and practices in Ghana? The study observed that there are several tangible and intangible evaluative dimensions that are deeply-rooted in cultural values, maxims, norms and other social patterns within the indigenous communities. Consequently, comparable dimensions could be advanced and established in the present evaluation research to add further depth and rigour to the study in this field.
Extensions of d'Alembert's paradox for elongated bodies

The steady incompressible irrotational flow past a three-dimensional body of any shape generates no forces. The historic paradox refers only to drag, but lift is also zero, which has been known but not emphasized. The new material concerns a body with a long constant cross section, such as a train. The final results for forces and moments are very simple. With zero angle of attack, we show that the force vectors on the front and rear parts of the body are each (asymptotically) equal to zero, if the pressure is referred to the freestream pressure. The lift and drag coefficients, based on frontal area, vanish proportionally to d/l and (d/l)2, respectively, where d/l is the diameter-to-length ratio. This applies to any shape of the cross section, and of the ends. With an angle of attack, the nose and tail forces are non-zero but depend only on the angle of attack and the cross section's added mass per unit length. The pitching moment is proportional to the total added mass and the sine of twice the angle of attack. The present results clarify slender-body theory results. The practical consequence is that, for a long body with constant cross section, the shape of the nose or the tail is irrelevant to its own ‘partial’ drag and lift, and to the pitching moment.
Quality of Life of Cancer Patients during Chemotherapy in Indonesia: A Comparison of EORTC QLQ-C30 and EQ-5D-5L, Based on Patients' Characteristics

One of the important outcomes to define the success of cancer treatment is the health-related quality of life (HRQoL) that can be measured using generic and/or specific instruments. Our study aims to define the cancer patients' HRQoL in some hospitals in Indonesia as measured by the European Organization for Research and Treatment for Cancer (EORTC QLQ-C30) and the EQ-5D-5L, to define the differences of cancer patients' HRQoL referring to patients' characteristics, and to explore determinants of cancer patients' HRQoL. We recruited 451 cancer patients using a cross-sectional design in two referral hospitals in Central Java, Indonesia, using the purposive sampling technique. All subjects, recruited from July 2020 to October 2021, met the inclusion criteria, namely, adult patients diagnosed with cancers in all stages who willingly participated in the study. The Indonesian value set was used to obtain the EQ-5D-5L index score. We further analyzed the data based on cancer stages and compared two questionnaires using independent t test. We highlighted that most of the cancer patients are female (69.4%), young (86%), and at advanced stages of cancer (54.1%). The physical and role functions and global health status of the cancer patients are poor, and the most severe symptom is fatigue. Moreover, most of them experience severe pain and perform daily activities with difficulties. Some patients' characteristics show significant influences on the HRQoL domains in both questionnaires (p < 0.05). Interestingly, both of the questionnaires have shown significant correlations between similar domains and revealed the poor HRQoL of advanced cancer patients (p < 0.05). Our study finds that cancer patients still have poor HRQoL in some domains. We suggest to the health providers that they apply education and psychological intervention to increase their HRQoL.
Aperture synthesis mapping of molecular gas in high-luminosity IRAS galaxies

The Owens Valley millimeter-wave interferometer has been used for high-resolution mapping of the 2.6 mm CO emission from the high-luminosity infrared galaxies NGC 520 (Arp 157), NGC 7469 (Arp 298), and Arp 55. Assuming the same empirical relationship between CO brightness and molecular hydrogen surface mass density as has been found for giant molecular clouds in the Milky Way, it is found that the masses of H2 gas in these concentrations are 10 to the 9th - 10 to the 10th solar masses, typically one-third of the total molecular gas content of these galaxies. The interferometric sizes correspond to radii of 0.8 kpc (NGC 520), 1.4 kpc (NGC 7469), and less than 2.8 kpc (Arp 55). For the same regions the dynamical masses estimated from the CO line width and size of the emission region are only a factor of 3-5 higher. The mean molecular gas surface densities averaged over these regions are in the range 610-825 solar masses/sq pc, a factor of 10 brighter than those obtained for corresponding regions in the nucleus of the Milky Way. The high mass fractions obtained for the interstellar medium in the central regions of these three galaxies strongly suggest that large-scale gravitationalmore » instability in the gas may play an important role in the further concentration of the gas in the nucleus and in possibly precipitating a large-scale burst of star formation. 34 references. « less
State of Health Estimation Methods for Lithium-Ion Batteries

Contemporary lithium-ion batteries (LIBs) are one of the main components of energy storage systems that need effective management to extend service life and increase reliability and safety. Their characteristics depend highly on internal and external conditions (ageing, temperature, and chemistry). Currently, the state of batteries is determined using two parameters: the state of charge (SOC) and the state of health (SOH). Applying these two parameters makes it possible to calculate the expected battery life and a battery’s performance. There are many methods for estimating the SOH of batteries, including experimental, model-based, and machine learning methods. By comparing model-based estimations with experimental techniques, it can be concluded that the use of experimental methods is not applicable for commercial cases. The electrochemical model-based SOH estimation method clearly explains processes in the battery with the help of multidifferential equations. The machine learning method is based on creating a program trained to predict the battery’s state of health with the help of past ageing data. In this review paper, we analyze the research available in the literature in this direction. It is found that all methods used to assess the SOH of an LIB play an essential role, and each method has its pros and cons.
Fully Convolutional Neural Network for Event Camera Pose Estimation

: Event cameras are bio-inspired vision sensors that record the dynamics of a scene while filtering out unnecessary data. Many classic pose estimation methods have been superseded by camera relocalization approaches based on convolutional neural networks (CNN) and long short-term memory (LSTM) in the investigation of simultaneous localization and mapping systems. However, and due to the usage of LSTM layer these methods are easy to overfit and usually take a long time to converge. In this paper, we introduce a new method to estimate the 6DOF pose of an event camera with a deep learning. Our approach starts by processing the events and generates a set of images. It then uses two CNNs to extract relevant features from the generated images. Those features are multiplied using the outer product at each location of the image and pooled across locations. The model ends with a regression layer which outputs the estimated position and orientation of the event camera. Our approach has been evaluated on different datasets. The results show its superiority compared to state-of-the-art methods.
The influence of the large-scale interplanetary shock structure on a low-energy particle event

We have developed a numerical model to study the influence of the large-scale shock topology on the associated low-energy (less than 2 MeV) particle event upstream of the shock. It includes particle injection at the solar corona, two-dimensional MHD simulation of the propagation of the shock, modeling of particle propagation through the interplanetary medium, and particle injection at the shock. The model does not attempt to simulate the physical processes of shock particle acceleration, therefore the injection at the shock is represented by a numerical source function in the equation that describes particle propagation
Mainstreaming Indigenous Knowledge Systems and Practices in Climate-Sensitive Policies for Resilient Agricultural Systems in Ghana

Abstract Policymakers underestimate the extensive role of indigenous and local knowledge (ILK) in national climate adaptation action. Drawing from the mainstreaming theory, this study examined the extent to which ILK systems have been mainstreamed into Ghana’s climate policy framework for realizing adaptation outcomes in agriculture and rural development. The study employed qualitative approaches including content analysis of policy documents and 15 key informant interviews. Findings revealed that adaptation actions are only canvassed in the national actions for climate change adaptation but are spirally incorporated in agriculture and rural development policies which are critical adaptation areas for Ghana as emphasized in the National Climate Change Policy. Further, results suggested that ILK is less prioritized in Ghana’s policy framework despite its importance and emergence in local adaptation efforts. Finally, the results revealed inadequate information on ILK, lack of deliberate policy on ILK and practices, lack of government commitment toward ILK, under-sourced institutions and Lack of coordination and inherent overlap of mandate as key barriers militating against mainstreaming ILK and climate change adaptation in national policy. We conclude that mainstreaming ILK and local adaptation practices in Ghana’s climate policy has the potential to facilitate a collective and sustainable response to climate change and build resilient agricultural systems to address food security challenges and foster rural development.
Phototransition of Na(3p3/2) into high Rydberg states and the ionization continuum

A model potential method is used to investigate photoabsorption from the Na(3p3/2) state. Absorption cross sections into higher Rydberg states and photoionization cross sections are presented as an analytical function of photo electron energy. Einstein coefficients for spontaneous emissions 3p3/2 ← ns1/2, nd5/2, nd3/2 are tabulated for n up to 50. The Einstein coefficients and low-energy ionization cross sections are believed to be accurate to better than 2–3%, above 1 eV the error may increase to 4–6%.
Simulations and Measurements of Pressure Oscillations Caused by Vortex Ropes

Pressure oscillations caused by vortex rope were measured in the draft tube of a prototype Francis turbine. The three-dimensional, unsteady Reynolds-averaged Navier-Stokes equations with the RNG κ- ∈ turbulence model were solved to model the flow within the entire flow path of the prototype hydraulic unit including the guide vanes, the runner, and the draft tube. The model was able to predict the pressure fluctuations that occur when operating at 67-83% of the optimum opening. The calculated frequencies and amplitudes of the oscillation show reasonable agreement with the experiment data. However, the results at 50% opening were not satisfactory. Pressure oscillations on the runner blades were found to be related to the precession of vortex ropes which caused pressure on the blades to fluctuate with frequencies of -f n +f d (f n is the rotational frequency and f d is vortex procession frequency). The peak-to-peak amplitudes of the pressure oscillations on the blades at the lower load conditions (67% opening) were higher than at higher load conditions (83% opening). Fluctuations on the suction side tended to be stronger than on the pressure side.
On the instability of a free viscous rim

This paper is devoted to the theoretical description of the dynamics of a rim formed by capillary forces at the edge of a free, thin liquid sheet. The rim dynamics are described using a quasi-one-dimensional approach accounting for the inertia of the liquid in the rim and for the liquid flow entering the rim from the sheet, surface tension and viscous stresses. The governing equations are derived from the mass, momentum and moment-of-momentum-balance equations of the rim. The theory provides a basis from which to analyse the linear stability of a straight line rim bounding a planar liquid sheet. The combined effect of the axisymmetric disturbances of the radius of the rim cross-section as well as of the transverse disturbances of the rim centreline is considered. The effect of the viscosity, relative film thickness and rim deceleration are investigated. The predicted wavelength of the most unstable mode is always very similar to the Rayleigh wavelength of the instability of an infinite cylindrical jet. This prediction is confirmed by various experimental data found in the literature. The maximum rate of growth of rim disturbances depends on all the parameters of the problem; however, the most pronounced effect can be attributed to the rim deceleration. This conclusion is confirmed by nonlinear simulations of rim deformation.
Mapping Extremely Low Metallicity Galaxies to Redshift One

We describe the results of a narrowband search for ultrastrong emission line galaxies (USELs) with EW(Hβ) ≥ 30 Å. A total of 542 candidate galaxies are found in a one-half square degree survey using two ~120 Å filters centered at 8150 and 9140 Å with Subaru SuprimeCam. Follow-up spectroscopy for randomly selected objects in the candidate sample with Keck II DEIMOS shows that they consist of [O III] λ5007-, [O II] λ3727-, and Hα-selected strong emission line galaxies at intermediate redshift (z < 1) and Lyα-emitting galaxies at high redshift (z ≫ 5). We determine the Hβ luminosity functions and the star formation density of the USELs, which is 5%-10% of the value found from ultraviolet continuum objects at z = 0-1, suggesting that they correspond to a major epoch in the galaxy formation process at these redshifts. Many of the USELs show the temperature-sensitive [O III] λ4363 auroral lines, and about a dozen have oxygen abundances satisfying the criteria of extremely metal-poor galaxies (XMPGs). These XMPGs are the most distant known today. Our high yield rate of XMPGs suggests that the narrowband method is a powerful way to find such populations. Moreover, the lowest metallicity measured in our sample is close to the minimum metallicity found in local galaxies [12 + log(O/H) ~ 7.1], although we need deeper spectra to minimize the errors. HST ACS images of several USELs exhibit widespread morphologies from relatively compact high surface brightness objects to very diffuse low surface brightness ones. The luminosities, metallicities, and star formation rates of USELs are consistent with the strong emitters being start-up intermediate-mass galaxies that will evolve into more normal galaxies and suggest that galaxies are still forming in relatively chemically pristine sites at z < 1.
Vibration Reduction Using Multi-Hump Input Shapers

Input shaping is a method for reducing residual vibrations in computer-controlled machines. Vibration is eliminated by convolving an input shaper, which is a sequence of impulses, with a desired system command to produce a shaped input. The shaped input then becomes the command to the system. Requiring the vibration reduction to be robust to modeling errors and system nonlinearities is critical to the success of the shaping process on any real system. Input shapers can be made very insensitive to parameter uncertainty; however, increasing robustness usually increases system delays. A design process is presented that generates input shapers with insensitivity-to-time-delay ratios that are much larger than traditionally designed input shapers. The advantages of the new shapers are demonstrated with computer simulations and their performance is verified with experimental results from the MIT Middeck Active Control Experiment, which was performed on board the Space Shuttle Endeavor.
Variations of stable isotope in Typhoon Lupit (2021) rainfall and its response to upstream convective processes

Typhoons produce a large amount of rainfall with a highly depleted isotopic composition. However, the mechanisms of isotope fractionation during typhoons remain poorly understood. Here, we present the hourly resolution isotope composition of rainfall during Typhoon Lupit (2021) in Fuzhou, on the southeast coast of China, to better understand these processes. Our results showed that the rainfall of Typhoon Lupit had significant fluctuations in δ18O values, ranging from −20.1‰ to −6.3‰, and exhibited a three‐stage variation with distinctly negative δ18O values in the second stage. In the first stage of Lupit, water vapour originated primarily from the nearby sea area, which did not undergo sustained convective activity, resulting in relatively enriched δ18O values. In the second stage, the δ18O values were extremely negative mainly because of the accumulated convective activity and continuous precipitation as they travelled towards the centre of the typhoon. In the third stage, the mixing of more localized and nearby sea water vapour caused an increase in the δ18O values. In summary, the three‐stage characteristics of Typhoon Lupit were largely caused by the integration of accumulated convective activity and moisture sources. Our findings reveal how upstream rainout affects the isotopic behaviour of rainfall and may have implications for understanding the dynamics of typhoon rainfall isotopes.