Miracle-dz/UniFAR-FTUs huggingface dataset:
Relay: A High-Level IR for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) models have recently enabled progress in areas like computer vision and natural language processing. Extending these frameworks to accommodate the rapidly diversifying landscape of DL models and hardware platforms presents challenging tradeoffs between expressiveness, composability, and portability. We present Relay, a new intermediate representation (IR) and compiler framework for DL models. The functional, statically-typed Relay IR unifies and generalizes existing DL IRs and can express state-of-the-art models. Relay's expressive IR required careful design of the type system, automatic differentiation, and optimizations. Relay's extensible compiler can eliminate abstraction overhead and target new hardware platforms. The design insights from Relay can be applied to existing frameworks to develop IRs that support extension without compromising on expressivity, composibility, and portability. Our evaluation demonstrates that the Relay prototype can already provide competitive performance for a broad class of models running on CPUs, GPUs, and FPGAs.
Increasing PV Hosting Capacity With an Adjustable Hybrid Power Flow Model

Physical constraints must be enforced when distributed energy resources, such as PV, are integrated into distribution network. Hosting capacity (HC) is thus introduced to define the maximum renewable generation that distribution system can accommodate. When the grid is further pushed towards decarbonization, improving HC becomes even more important. This work presents a hybrid adjustable power flow model to increase the uncertainty-proof HC, aiming to securely and cost-effectively utilize flexible resources. We propose a novel hybrid relaxation approach to convexifying a two-stage AC model with variable uncertainty set. An iterative algorithm is designed to solve the problem. We perform the case study in a single-phase 141-node system and a three-phase 33-bus system. The proposed approach shows promising performance in accuracy, convergence, and robustness.
End-to-End Learning of Representations for Asynchronous Event-Based Data

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events”. They have appealing advantages over frame based cameras for computer vision, including high temporal resolution, high dynamic range, and no motion blur. Due to the sparse, non-uniform spatio-temporal layout of the event signal, pattern recognition algorithms typically aggregate events into a grid-based representation and subsequently process it by a standard vision pipeline, e.g., Convolutional Neural Network (CNN). In this work, we introduce a general framework to convert event streams into grid-based representations by means of strictly differentiable operations. Our framework comes with two main advantages: (i) allows learning the input event representation together with the task dedicated network in an end to end manner, and (ii) lays out a taxonomy that unifies the majority of extant event representations in the literature and identifies novel ones. Empirically, we show that our approach to learning the event representation end-to-end yields an improvement of approximately 12% on optical flow estimation and object recognition over state-of-the-art methods.
The Difference between Problem Based Learning Model and Discovery Learning Model on Students' Critical Thinking Ability

The success of teachers in carrying out the learning process is influenced by several factors, one of which is the accuracy in the selection of learning models. This study aims to analyze the differences between the PBL model and the discovery learning model in improving students' critical thinking skills. The sample of this research is 27 students. This research is an experimental study using a non-equivalent control group design. The instrument used to measure critical thinking skills is a questionnaire. Prerequisite test using normality test and homogeneity test. Data analysis used t-test (t-test for independent samples). The results showed that there were significant differences in students' critical thinking skills using the PBL model and the discovery learning model in fourth grade students. The difference in the average score of critical thinking skills in the PBL model gets an average score of 68.44, and the discovery learning model gets an average score of 57.09. Therefore, the PBL model can be interpreted as superior to the discovery learning model in terms of critical thinking skills. This is supported by the results of the t-test which has a sig (two-sided) value of 0.000 < 0.05, Ho is rejected and Ha is accepted. This means that the critical thinking ability of the PBL model is significantly more effective than the discovery learning model.
Optical spectral index - luminosity relation for the 17 mapped Palomar-Green quasars

In this paper, the optical spectra index-luminosity relationship is checked for the well-known 17 individually mapped quasi-stellar objects (QSOs), in order to give one more clearer conclusion on the so far conflicting dependence of the spectral index on the luminosity for an active galactic nucleus (AGN). Unlike the global relationships based on the colour difference (photometry parameters) for samples of AGNs, a more reliable relationship is determined for the multi-epoch observed individually mapped QSOs with no contamination from the host galaxies, the line variabilities and the very different central properties. The final confirmed results are as follows. (i) No strong dependence of the optical spectral index on the continuum luminosity can be found for all 17 QSOs, besides two objects (PG 0026 and PG 1613) that have some weak trends (with 3 Sigma confidence level) for the relationship. In other words, the common expectation that 'AGNs get bluer when they get brighter' is not so common. (ii) There are very different damped intrinsic variability time-scales for the variability modes of the optical spectral index and the continuum emission, through the well-applied damped random walk method for the AGN variability. In other words, there are some different intrinsic mechanisms controlling the variabilities of the optical spectral index and the power-law AGN continuum emission. Therefore, the much weaker dependence of the optical spectral index on the continuum luminosity can be further confirmed.
A Non-Convex Compressed Sensing Model Improving the Energy Efficiency of WSNs for Abnormal Events’ Monitoring

The wireless sensor network (WSN), a communication system widely used in the Internet of Things, usually collects physical data in a natural environment and monitors abnormal events. Because of the redundancy of natural data, a compressed-sensing-based model offers energy-efficient data processing to overcome the energy shortages and uneven consumption problems of a WSN. However, the convex relaxation method, which is widely used for a compressed-sensing-based WSN, is not sufficient for reducing data processing energy consumption. In addition, when abnormal events occur, the redundancy of the original data is destroyed, which makes the traditional compressed sensing methods ineffective. In this paper, we use a non-convex fraction function as the surrogate function of the ℓ0-norm, which achieves lower energy consumption of the sensor nodes. Moreover, considering abnormal event monitoring in a WSN, we propose a new data construction model and apply an alternate direction iterative thresholding algorithm, which avoids extra measurements, unlike previous algorithms. The results showed that our models and algorithms reduced the WSN’s energy consumption during abnormal events.
About the ergodic regime in the analogical Hopfield neural networks: Moments of the partition function

In this paper we introduce and exploit the real replica approach for a minimal generalization of the Hopfield model by assuming the learned patterns to be distributed according to a standard unit Gaussian. We consider the high storage case, when the number of patterns linearly diverges with the number of neurons. We study the infinite volume behavior of the normalized momenta of the partition function. We find a region in the parameter space where the free energy density in the infinite volume limit self-averages around its annealed approximation, as well as the entropy and the internal energy density. Moreover, we evaluate the corrections to their extensive counterparts with respect to their annealed expressions. The fluctuations of properly introduced overlaps, which act as order parameters, are also discussed.
Sox9 Expression in the Second Heart Field; A Morphological Assessment of the Importance to Cardiac Development with Emphasis on Atrioventricular Septation

Failure to form the septal structures that separate the left and right cardiac chambers results in defects that allow shunting of blood from one side of the heart to the other, leading to the mixing of oxygenated and de-oxygenated blood. The atrioventricular (AV) mesenchymal complex, consisting of the AV cushions, the Dorsal Mesenchymal Protrusion (DMP), and the mesenchymal cap, plays a crucial role in AV septation. Cells found in these structures derive from different cell lineages. In this study we have investigated the role of the transcription factor Sox9 in the Second Heart Field (SHF) with the emphasis on the formation of the atrioventricular septal complex. Using a mouse model in which Sox9 is conditionally deleted from the SHF we demonstrate that in this model virtually all mouse embryos develop septal abnormalities, including complete atrioventricular septal defects (cAVSDs) and isolated ventricular septal defects. Our morphological analyses indicate that perturbation of the development of the mesenchymal cap appears to play a crucial role in the pathogenesis of the atrial septal defects observed in the AVSDs and suggests that this component of the AV mesenchymal complex might play a more important role in AV septation than previously appreciated.
THE ROLE OF ICE COMPOSITIONS FOR SNOWLINES AND THE C/N/O RATIOS IN ACTIVE DISKS

The elemental compositions of planets define their chemistry, and could potentially be used as beacons for their formation location if the elemental gas and grain ratios of planet birth environments, i.e., protoplanetary disks, were well understood. In disks, the ratios of volatile elements, such as C/O and N/O, are regulated by the abundance of the main C, N, O carriers, their ice binding environment, and the presence of snowlines of major volatiles at different distances from the central star. We explore the effects of disk dynamical processes, molecular compositions and abundances, and ice compositions on the snowline locations of the main C, O, and N carriers, and the C/N/O ratios in gas and dust throughout the disk. The gas-phase N/O ratio enhancement in the outer disk (exterior to the H2O snowline) exceeds the C/O ratio enhancement for all reasonable volatile compositions. Ice compositions and disk dynamics individually change the snowline location of N2, the main nitrogen carrier, by a factor of 2–3, and when considered together the range of possible N2 snowline locations is ∼11–∼79 au in a standard disk model. Observations that anchor snowline locations at different stages of planet formation are therefore key to developing C/N/O ratios as a probe of planet formation zones.
Strong Subadditivity and Emergent Surface

In this paper, we introduce two bounds which we call the Upper Differential Entropy and the Lower Differential Entropy for an infinite family of intervals(strips) in quantum field theory. The two bounds are equal provided that the theory is translational invariant and the entanglement entropy varies smoothly with respect to the interval. When the theory has a holographic dual, strong subadditivity of entanglement entropy indicates that there is always an emergent surface whose gravitational entropy is exactly given by the bound.
Monocular-Vision-Based Precise Runway Detection Applied to State Estimation for Carrier-Based UAV Landing

Improving the level of autonomy during the landing phase helps promote the full-envelope autonomous flight capability of unmanned aerial vehicles (UAVs). Aiming at the identification of potential landing sites, an end-to-end state estimation method for the autonomous landing of carrier-based UAVs based on monocular vision is proposed in this paper, which allows them to discover landing sites in flight by using equipped optical sensors and avoid a crash or damage during normal and emergency landings. This scheme aims to solve two problems: the requirement of accuracy for runway detection and the requirement of precision for UAV state estimation. First, we design a robust runway detection framework on the basis of YOLOv5 (you only look once, ver. 5) with four modules: a data augmentation layer, a feature extraction layer, a feature aggregation layer and a target prediction layer. Then, the corner prediction method based on geometric features is introduced into the prediction model of the detection framework, which enables the landing field prediction to more precisely fit the runway appearance. In simulation experiments, we developed datasets applied to carrier-based UAV landing simulations based on monocular vision. In addition, our method was implemented with help of the PyTorch deep learning tool, which supports the dynamic and efficient construction of a detection network. Results showed that the proposed method achieved a higher precision and better performance on state estimation during carrier-based UAV landings.
Self-luminous and Irradiated Exoplanetary Atmospheres Explored with HELIOS

We present new methodological features and physical ingredients included in the one-dimensional radiative transfer code HELIOS, improving the hemispheric two-stream formalism. We conduct a thorough intercomparison survey with several established forward models, including COOLTLUSTY and PHOENIX, and find satisfactory consistency with their results. Then, we explore the impact of (i) different groups of opacity sources, (ii) a stellar path length adjustment, and (iii) a scattering correction on self-consistently calculated atmospheric temperatures and planetary emission spectra. First, we observe that temperature–pressure (T–P) profiles are very sensitive to the opacities included, with metal oxides, hydrides, and alkali atoms (and ionized hydrogen) playing an important role in the absorption of shortwave radiation (in very hot surroundings). Moreover, if these species are sufficiently abundant, they are likely to induce nonmonotonic T–P profiles. Second, without the stellar path length adjustment, the incoming stellar flux is significantly underestimated for zenith angles above 80°, which somewhat affects the upper atmospheric temperatures and the planetary emission. Third, the scattering correction improves the accuracy of the computation of the reflected stellar light by ∼10%. We use HELIOS to calculate a grid of cloud-free atmospheres in radiative–convective equilibrium for self-luminous planets for a range of effective temperatures, surface gravities, metallicities, and C/O ratios to be used by planetary evolution studies. Furthermore, we calculate dayside temperatures and secondary eclipse spectra for a sample of exoplanets for varying chemistry and heat redistribution. These results may be used to make predictions on the feasibility of atmospheric characterizations with future observations.
Unisel Foundation Students’ Attitude Towards E-Learning As A Sustainable Platform Of Education

The Covid-19 pandemic has forced education institutions to adopt online platforms for teaching and learning. Online education platforms are web or digital based applications which enable users to conduct and attend classes virtually. The implementation of online classes through online platforms was sudden and rushed due to the increase and the prolonging of covid-19 cases. Over the past year, these online platforms have become an essential tool in continuing the teaching and learning process across numerous educational sectors. This paper intended to explain the students’ attitude towards using e-learning platforms as a sustainable platform of education and at the same time explore their perception of using e-learning as a sustainable tool. A set of questionnaires is administered to 159 foundation students in Universiti Selangor, and the data obtained is statistically analysed to fulfil the research objectives. As online education becomes an essential part of education, it is crucial to understand the sustainability of online pedagogy and the impact it has on the students. Students may not have the same level of acceptance and views towards the use of online platforms. The outcome of this study will assist educators and administrators in planning and using online platforms to conduct online classes that suit the needs and expectations of the students .
The Effect of Toxic Relationships in Friendship on The Psychological Well-Being of Islamic University Students

Good psychological well-being is characterized by individuals who have positive emotions and can go through difficult times that cause negative emotions to emerge. Data obtained from Riskesdas (Riset Kesehatan Dasar), in 2007 about 11.6% of the Indonesian population aged over 15 years showed emotional mental disorders characterized by symptoms of depression and anxiety. Then in 2018 the prevalence of emotional mental disorders again increased to around 9.8% (Idaiani & Isfandari, 2020). One of the factors that influence it is social support that comes from friends. Support from friends is not always positive, but also negative. Negative friends are referred to as toxic friends, namely friendships that are detrimental. The aims of this study are, (1) to describe the level of psychological well-being of Islamic University Students, (2) to describe the level of toxic relationships that occur in the circle of friends of Islamic University Students, and (3) to analyze the effect of toxic relationships on psychological well-being. to students of Islamic University Students. The method used for this research is simple regression. With a population of 11,000 people and a sample of 265 students aged 18-22 years. The results of this study are, (1) the level of psychological well-being in Islamic University Students is dominated by the very high category as many as 155 students with a percentage of 58.5%, (2) the level of toxic relationship among Islamic University Students is dominated by the low category as much as 140 students with a percentage of 52.8%, (3) there is an influence between variables toxic relationships and psychological well-being with effect level of 11.4%. Although it does not have a big influence, it is important for us to control a healthy friendship environment to maintain psychological well-being in ourselves.
Phase diagram of the antiferromagnetic XXZ model on the triangular lattice

We determine the quantum phase diagram of the antiferromagnetic spin-1/2 XXZ model on the triangular lattice as a function of magnetic field and anisotropic coupling $J_z$. Using the density matrix renormalization group (DMRG) algorithm in two dimensions we establish the locations of the phase boundaries between a plateau phase with 1/3 N\'eel order and two distinct coplanar phases. The two coplanar phases are characterized by a simultaneous breaking of both translational and U(1) symmetries, which is reminiscent of supersolidity. A translationally invariant umbrella phase is entered via a first order phase transition at relatively small values of $J_z$ compared to the corresponding case of ferromagnetic hopping and the classical model. The phase transition lines meet at two tricritical points on the tip of the lobe of the plateau state, so that the two coplanar states are completely disconnected. Interestingly, the phase transition between the plateau state and the upper coplanar state changes from second order to first order for large values of $J_z > 2.5J$.
Development of display and disposal work system for convenience stores using dual-arm robot

ABSTRACT Labor shortages have been reported in numerous developed economies, and they are becoming increasingly severe, particularly in convenience stores. An important task in a convenience store is the display and disposal of a wide variety of products. However, there are technological gaps between the present technology and the expected setup. To solve the demand for the display and disposal tasks in convenience stores, ‘World Robot Summit Future Convenience Store Challenge(WRS FCSC)’ was established in 2017. The tasks of WRS FCSC are important; however, it is difficult to completely achieve the required tasks because the tasks in convenience stores are optimized for human workers. In this study, we first analyze the functions required to solve the problems of tasks in WRS FCSC. Through the analysis, we have developed several system components including two kinds of grippers for dual-arm and its manipulation strategy, intelligent shelf with manipulation support function and human detection function surrounding the shelf, object pose detection algorithm, precise autonomous navigation strategy, and management system to integrate the all the components. The effectiveness of the developed system is evaluated through the same scenario of WRS FCSC. Through the experiment, we confirmed the effectiveness our developed system. GRAPHICAL ABSTRACT
Stochastic reacceleration of relativistic electrons by turbulent reconnection: a mechanism for cluster-scale radio emission?

In this paper we investigate a situation where relativistic particles are reaccelerated diffusing across regions of reconnection and magnetic dynamo in super-Alfvenic, incompressible large-scale turbulence. We present an exploratory study of this mechanism in the intra-cluster-medium (ICM). In view of large-scale turbulence in the ICM we adopt a reconnection scheme that is based on turbulent reconnection and MHD turbulence. In this case particles are accelerated and decelerated in a systematic way in reconnecting and magnetic-dynamo regions, respectively, and on longer time-scales undergo a stochastic process diffusing across these sites (similar to second-order Fermi). Our study extends on larger scales numerical studies that focused on the acceleration in and around turbulent reconnecting regions. We suggest that this mechanism may play a role in the reacceleration of relativistic electrons in galaxy clusters providing a new physical scenario to explain the origin of cluster-scale diffuse radio emission. Indeed differently from current turbulent reacceleration models proposed for example for radio halos this mechanism is based on the effect of large-scale incompressible and super-Alfvenic turbulence. In this new model turbulence governs the interaction between relativistic particles and magnetic field lines that diffuse, reconnect and are stretched in the turbulent ICM.