Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Knowledge Tracing

High-quality education is one of the keys to achieving a more sustainable world. The recent COVID-19 epidemic has triggered the outbreak of online education, which has enabled both students and teachers to learn and teach at home. Meanwhile, it is now possible to record and research a large amount of learning data using online learning platforms in order to offer better intelligent educational services. Knowledge Tracing (KT), which aims to monitor students' evolving knowledge state, is a fundamental and crucial task to support these intelligent services. Therefore, an increasing amount of research attention has been paid to this emerging area and considerable progress has been made. In this survey, we propose a new taxonomy of existing basic KT models from a technical perspective and provide a comprehensive overview of these models in a systematic manner. In addition, many variants of KT models have been proposed to capture more complete learning process. We then review these variants involved in three phases of the learning process: before, during, and after the student learning, respectively. Moreover, we present several typical applications of KT in different educational scenarios. Finally, we provide some potential directions for future research in this fast-growing field.
Dilute magnetic moments in an exactly solvable interacting host

Despite concerted efforts, the problem of dilute local moments embedded in a correlated conduction electron host such as Nd1−xCexCuO2 persists due to lack of analytically controllable models. Here, we address the question: how do local moments couple to correlated but integrable hosts? We describe the conduction electrons by the model of Hatsugai-Kohmoto (HK) which has undergone a recent resurgence arising from its exact solvability, existence of Luttinger surfaces, and connections to Sachdev-Ye-Kitaev (SYK) thermodynamics. We derive an exact low energy “Kondo-HK” Hamiltonian and show the existence of additional spin-exchange coupling that is relevant in the renormalization group (RG) sense. This term is ferromagnetic and does not vanish at low energies yielding an algebraic enhancement of the Kondo temperature. “Poor man’s” scaling of couplings exhibits an exotic step-like RG flow between UV-IR fixed points attributed to severely restricted scattering phase space. This phenomenon is analogous to the flow of central charge in Zamolodchikov’s diagonal resonance scattering in integrable quantum field theories.
Effects of the Linear Polarization of Polariton Condensates in Their Propagation in Codirectional Couplers

We report on the linear polarization of polariton condensates in a codirectional coupler that allows evanescent coupling between adjacent waveguides. During the condensate’s formation, polaritons usually acquire a randomly oriented polarization, however, our results reveal a preferential orientation of the linear polarization along the waveguide propagation path. Furthermore, we observe polarization-dependent intensity oscillations in the output terminal of the coupler, and we identify the mode beating between the linear-polarized eigenmodes as the origin of these oscillations. Our findings provide an insight into the control of the polarization of polariton condensates, paving the way for the development of spin-based polaritonic architectures where condensates propagate over macroscopic distances.
Impact of Public and Private Investments on Economic Growth of Developing Countries

This paper aims to study the impact of public and private investments on the economic growth of developing countries. The study uses the panel data of 39 developing countries covering the periods 1990-2019. The study was based on the neoclassical growth models or exogenous growth models state in which land, labor, capital accumulation, etc., and technology proved substantial for economic growth. The paper finds that public investment has a strong positive impact on economic growth than private investment. Gross capital formation, labor growth, and government final consumption expenditure were found significant in explaining the economic growth. Overall, both public and private investments are substantial for the economic growth and development of developing countries.
VersatileGait: A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation

Gait recognition has a rapid development in recent years. However, gait recognition in the wild is not well explored yet. An obvious reason could be ascribed to the lack of diverse training data from the perspective of intrinsic and extrinsic factors. To remedy this problem, we propose to construct a large-scale gait dataset with the help of controllable computer simulation. In detail, to diversify the intrinsic factors of gait, we generate numerous characters with diverse attributes and empower them with various types of walking styles. To diversify the extrinsic factors of gait, we build a complicated scene with a dense camera layout. Finally, we design an automated generation toolkit under Unity3D for simulating the walking scenario and capturing the gait data automatically. As a result, we obtain an in-the-wild gait dataset, called VersatileGait, which has more than one million silhouette sequences of 10,000 subjects with diverse scenarios. VersatileGait possesses several nice properties, including huge dataset size, diverse pedestrian attributes, complicated camera layout, high-quality annotations, small domain gap with the real one, good scalability for new demands, and no privacy issues. Based on VersatileGait, we propose series of experiments and applications for both research exploration of gait in the wild and practical applications. Our dataset and its corresponding generation toolkit will be publicly available for further studies.
Phase‐field modeling of rock fractures with roughness

Phase‐field modeling—a continuous approach to discontinuities—is gaining popularity for simulating rock fractures due to its ability to handle complex, discontinuous geometry without an explicit surface tracking algorithm. None of the existing phase‐field models, however, incorporates the impact of surface roughness on the mechanical response of fractures—such as elastic deformability and shear‐induced dilation—despite the importance of this behavior for subsurface systems. To fill this gap, here we introduce the first framework for phase‐field modeling of rough rock fractures. The framework transforms a displacement‐jump‐based discrete constitutive model for discontinuities into a strain‐based continuous model, without any additional parameter, and then casts it into a phase‐field formulation for frictional interfaces. We illustrate the framework by constructing a particular phase‐field form employing a rock joint model originally formulated for discrete modeling. The results obtained by the new formulation show excellent agreement with those of a well‐established discrete method for a variety of problems ranging from shearing of a single discontinuity to compression of fractured rocks. It is further demonstrated that the phase‐field formulation can well simulate complex crack growth from rough discontinuities. Consequently, our phase‐field framework provides an unprecedented bridge between a discrete constitutive model for rough discontinuities—common in rock mechanics—and the continuous finite element method—standard in computational mechanics—without any algorithm to explicitly represent discontinuity geometry.
Digital Contact Tracing for Covid 19

The COVID19 pandemic created a worldwide emergency as it is estimated that such a large number of infections are due to human-to-human transmission of the COVID19. As a necessity, there is a need to track users who came in contact with users having travel history, asymptomatic and not yet symptomatic, but they can be in the future. To solve this problem, the present work proposes a solution for contact tracing based on assisted GPS and cloud computing technologies. An application is developed to collect each user's assisted GPS coordinates once all the users install this application. This application periodically sends assisted GPS data to the cloud. To determine which devices are within the permissible limit of 5m, we perform clustering over assisted GPS coordinates and track the clusters for about t mins to allow the measure of spread. We assume that it takes around 3 or 5 mins to get the virus from an infected object. For clustering, the proposed M way like tree data structure stores the assisted GPS coordinates in degree, minute, and second format. Thus, every user is mapped to a leaf node of the tree. We split the "seconds" part of the assisted GPS location into m equal parts, which amount to d meter in latitude(longitude). Hence, two users who are within d meter range will map to the same leaf node. Thus, by mapping assisted GPS locations every t mins, we can find out how many users came in contact with a particular user for at least t mins. Our work's salient feature is that it runs in linear time O(n) for n users in the static case, i.e., when users are not moving. We also propose a variant of our solution to handle the dynamic case, that is, when users are moving. Besides, the proposed solution offers potential hotspot detection and safe-route recommendation as an additional feature, and proof of concept is presented through experiments on simulated data of 10M users.
The Impact of Pore-Size Heterogeneities on the Spatiotemporal Variation of Microbial Metabolic Activity in Porous Media

Abstract Natural porous media such as soils or aquifers are characterized by various pore-scale heterogeneities. This includes the temporal variability of substrate supply and the spatial heterogeneity of pore sizes. As a consequence, microbial growth conditions in natural porous medium environments may differ from typical laboratory setups used to study microbial behavior. Pore-size heterogeneities and the resulting transport regime can lead to highly complex distribution patterns of substrates and corresponding microbial growth conditions including the frequent occurrence of stress periods for the microbial population. Microorganisms can respond to such stress periods by switching from an active into an inactive or dormant state, and the corresponding microbial abundance and dynamics may exhibit rather complex temporal and spatial patterns. This study applies an extended modeling concept for the growth and degradation activity of microbial species able to switch between two different physiological states. The concept is implemented into a pore network model that allows simulating the changes in microbial growth conditions in heterogeneous porous media. The model is used to study the impact of pore-size heterogeneities on the distribution and activity of a bacterial community consisting of two competing species. Simulation results show that such pore-scale heterogeneity has a strong impact on bacterial abundance and activity, creating a complex structure of microbial niches. This leads to an increased coexistence of microbial species at both the microscale and the macroscale, although in the macroscale, the total biomass concentration is less affected by these heterogeneities.
Is Sluice Resolution really just Question Answering?

Sluice resolution is a problem where a system needs to output the corresponding antecedents of wh-ellipses. The antecedents are elided contents behind the wh-words but are implicitly referred to using contexts. Previous work frames sluice resolution as question answering where this setting outperforms all its preceding works by large margins. Ellipsis and questions are referentially dependent expressions (anaphoras) and retrieving the corresponding antecedents are like answering questions to output pieces of clarifying information. However, the task is not fully solved. Therefore, we want to further investigate what makes sluice resolution differ to question answering and fill in the error gaps. We also present some results using recent state-of-the-art question answering systems which improve the previous work (86.01 to 90.39 F1).
Securing IoT Devices by Exploiting Backscatter Propagation Signatures

The low-power radio technologies open up many opportunities to facilitate Internet-of-Things (IoT) into our daily life, while their minimalist design also makes IoT devices vulnerable to many active attacks. Recent advances use an antenna array to extract fine-grained physical-layer signatures to identify the attackers, which adds burdens in terms of energy and hardware cost to IoT devices. In this paper, we present ShieldScatter, a lightweight system that attaches low-cost tags to single-antenna devices to shield the system from active attacks. The key insight of ShieldScatter is to intentionally create multi-path propagation signatures with the careful deployment of tags. These signatures can be used to construct a sensitive profile to identify the location of the signals’ arrival, and thus detect the threat. In addition, we also design a tag-random scheme and a multiple receivers combination approach to detect a powerful attacker who has the strong priori knowledge of the legitimate user. We prototype ShieldScatter with USRPs and tags to evaluate our system in various environments. The results show that even when the powerful attacker is close to the legitimate device, ShieldScatter can mitigate 95 percent of attack attempts while triggering false alarms on just 7 percent of legitimate traffic.
DPLM: A Deep Perceptual Spatial-Audio Localization Metric

Subjective evaluations are critical for assessing the perceptual realism of sounds in audio-synthesis driven technologies like augmented and virtual reality. However, they are challenging to set up, fatiguing for users, and expensive. In this work, we tackle the problem of capturing the perceptual characteristics of localizing sounds. Specifically, we propose a framework for building a general-purpose quality metric to assess spatial localization differences between two binaural recordings. We model localization similarity by utilizing activation-level distances from deep networks trained for direction of arrival (DOA) estimation. Our proposed metric (DPLM) outperforms baseline metrics on correlation with subjective ratings on a diverse set of datasets, even without the benefit of any human-labeled training data.
Power and Performance Efficient SDN-Enabled Fog Architecture

Software defined networks (SDNs) have dramatically simplified network management. However, enabling pure SDNs to respond in real-time while handling massive amounts of data still remains a challenging task. In contrast, fog computing has strong potential to serve large surges of data in real time. SDN control plane enables innovation, and greatly simplifies network operations and management thereby providing a promising solution to implement energy and performance aware SDN-enabled fog computing. Besides, power efficiency and performance evaluation in SDN-enabled fog computing is an area that has not yet been fully explored by the research community. We present a novel SDN-enabled fog architecture to improve power efficacy and performance by leveraging cooperative and noncooperative policy-based computing. Preliminary results from extensive simulation demonstrate an improvement in the power utilization as well as the overall performance (i.e., processing time, response time). Finally, we discuss several open research issues that need further investigation in the future.
Dielectric Properties and Dispersion Parameters of Magnesium Oxide Nanoparticles with Temperature

Magnesium oxide (MgO) nanoparticles were synthesized through chemical coprecipitation followed by thermal treatment. Structural, optical and luminescence properties along with dielectric properties were studied and relaxation mechanisms were explored. The structural characterization studies confirmed the formation of nano sized MgO particles with hierarchical structures and high purity. The dielectric properties were studied in different frequency range at different temperatures. In addition, the Cole –Cole plot are used to explore the relaxation mechanism prevalent in nanostructured MgO. In dielectric materials there are multiple dipole relaxation mechanisms which give rises to spreading of relaxation time on the average relaxation time. © 2020 Elixir All rights reserved. Elixir Materials Science 148 (2020) 54942-54946 Materials Science Available online at www.elixirpublishers. com (Elixir International Journal) Sharmila P P/ Elixir Materials Science 148 (2020) 54942-54946 54943 be attributed to an increase in the particle size due to agglomeration at high temperature. The bandgap variations of the samples obtained are form 4.43 eV to 5.1 eV, but less than its bulk value 7 eV.
Anomalous thermopower oscillations in graphene-nanowire vertical heterostructures

Thermoelectric measurements have the potential to uncover the density of states (DOSs) of low-dimensional materials. Here, we present the anomalous thermoelectric behavior of monolayer graphene-nanowire (NW) heterostructures, showing large oscillations as a function of the doping concentration. Our devices consist of InAs NW and graphene vertical heterostructures, which are electrically isolated by thin (∼10 nm) hexagonal boron nitride (hBN) layers. In contrast to conventional thermoelectric measurements, where a heater is placed on one side of a sample, we use the InAs NW (diameter ∼50 nm) as a local heater placed in the middle of the graphene channel. We measure the thermoelectric voltage induced in graphene due to Joule heating in the NW as a function of temperature (1.5–50 K) and carrier concentration. The thermoelectric voltage in bilayer graphene (BLG)-NW heterostructures shows sign change around the Dirac point, as predicted by Mott’s formula. In contrast, the thermoelectric voltage measured across monolayer graphene (MLG)-NW heterostructures shows anomalous large-amplitude oscillations around the Dirac point, not seen in the Mott response derived from the electrical conductivity measured on the same device. The anomalous oscillations are a signature of the modified DOSs in MLG by the electrostatic potential of the NW, which is much weaker in the NW-BLG devices. Thermal calculations of the heterostructure stack show that the temperature gradient is dominant in the graphene region underneath the NW, and thus sensitive to the modified DOSs resulting in anomalous oscillations in the thermoelectric voltage. Furthermore, with the application of a magnetic field, we detect modifications in the DOSs due to the formation of Landau levels in both MLG and BLG.
Third retransplantation using a whole liver graft for late graft failure from hepatic vein stent stenosis in a pediatric patient who underwent split liver retransplantation

We present a case of third retransplantation using a whole liver graft in a 13-year-old girl who suffered graft failure and hepatopulmonary syndrome following split liver retransplantation with endovascular stenting of the hepatic and portal veins as an infant. She was diagnosed with biliary atresia-polysplenia syndrome, and thus underwent living donor liver transplantation from her mother at 9 months of age. The first liver graft failed due to stenosis of the portal vein. She underwent the second liver transplantation with a split left lateral section graft. Endovascular stenting was performed to the portal vein stenosis 2 months and hepatic vein stenosis 9 months after transplantation. During the next 9 years, 11 sessions of balloon angioplasty for hepatic vein stent stenosis were performed. Ten years after the second transplantation, she underwent third transplantation using a whole liver graft recovered from a 12-year-old-girl. The double inferior vena cava technique was used for outflow vein reconstruction. The graft portal vein was anastomosed with the stent-containing portal vein stump because it was not possible to remove the stent and the inner diameter of the portal vein stent was large enough. An aorto-hepatic jump graft was used for arterial reconstruction. The patient recovered slowly and is doing well for 6 months posttransplant. In conclusion, because stenting of the hepatic vein or portal vein can induce graft failure leading to late retransplantation, we emphasize secure vascular reconstruction to prevent endovascular stenting during LT in infants.
Acupuncture stimulation at HT7 as a non-pharmacological therapy for sleep disorder caused by caffeine administration in rats

Objectives: Insomnia is one of the most common sleep disorders and is difficult to completely treat because of the undesirable side effects of hypnotics. The present study was designed to investigate the hypnotic effect of acupuncture stimulation at HT7 on caffeine-induced sleep disorders and locomotor activity in rats. We also evaluated neuronal activity changes in the arousal region of the basal forebrain. Methods: Rats received intraperitoneal injections of caffeine, and then electroencephalogram power spectrum analysis and locomotor activity measurements were performed. Stimulation at HT7 was performed using a mechanical acupuncture instrument (MAI) before caffeine injection, and its effects on caffeine-induced changes in sleep architecture, locomotor activity and c-Fos expression were examined. Results: Caffeine injection (7.5 mg/kg) produced a significant decrease in slow-wave sleep and an increase in wake time compared with saline injection. Caffeine injection also increased locomotor activity and c-Fos expression in the medial septum–vertical limb of the diagonal band of Broca (MS-VDB), one of the arousal regions of the basal forebrain. Stimulation at HT7 with the MAI alleviated the caffeine-induced sleep disturbance and the increase in locomotor activity. In addition, MAI treatment at HT7, compared with treatment at a location not corresponding to any traditional acupuncture point, reduced the caffeine-induced increase in c-Fos expression. Conclusion: These results indicate that the hypnotic effect of HT7 acupuncture stimulation on caffeine-induced insomnia was associated with suppression of neuronal activity in the basal forebrain.
Head Shadow, Summation, and Squelch in Bilateral Cochlear-Implant Users With Linked Automatic Gain Controls

Speech understanding in noise is poorer in bilateral cochlear-implant (BICI) users compared to normal-hearing counterparts. Independent automatic gain controls (AGCs) may contribute to this because adjusting processor gain independently can reduce interaural level differences that BICI listeners rely on for bilateral benefits. Bilaterally linked AGCs may improve bilateral benefits by increasing the magnitude of interaural level differences. The effects of linked AGCs on bilateral benefits (summation, head shadow, and squelch) were measured in nine BICI users. Speech understanding for a target talker at 0° masked by a single talker at 0°, 90°, or −90° azimuth was assessed under headphones with sentences at five target-to-masker ratios. Research processors were used to manipulate AGC type (independent or linked) and test ear (left, right, or both). Sentence recall was measured in quiet to quantify individual interaural asymmetry in functional performance. The results showed that AGC type did not significantly change performance or bilateral benefits. Interaural functional asymmetries, however, interacted with ear such that greater summation and squelch benefit occurred when there was larger functional asymmetry, and interacted with interferer location such that smaller head shadow benefit occurred when there was larger functional asymmetry. The larger benefits for those with larger asymmetry were driven by improvements from adding a better-performing ear, rather than a true binaural-hearing benefit. In summary, linked AGCs did not significantly change bilateral benefits in cases of speech-on-speech masking with a single-talker masker, but there was also no strong detriment across a range of target-to-masker ratios, within a small and diverse BICI listener population.