Miracle-dz/UniFAR-FTUs huggingface dataset:
No Length Left Behind: Enhancing Knowledge Tracing for Modeling Sequences of Excessive or Insufficient Lengths

Knowledge tracing (KT) aims to predict students' responses to practices based on their historical question-answering behaviors. However, most current KT methods focus on improving overall AUC, leaving ample room for optimization in modeling sequences of excessive or insufficient lengths. As sequences get longer, computational costs will increase exponentially. Therefore, KT methods usually truncate sequences to an acceptable length, which makes it difficult for models on online service systems to capture complete historical practice behaviors of students with too long sequences. Conversely, modeling students with short practice sequences using most KT methods may result in overfitting due to limited observation samples. To address the above limitations, we propose a model called Sequence-Flexible Knowledge Tracing (SFKT). Specifically, to flexibly handle long sequences, SFKT introduces a total-term encoder to effectively model complete historical practice behaviors of students at an affordable computational cost. Additionally, to improve the prediction accuracy of students with short practice sequences, we introduce a contrastive learning task and data augmentation schema to improve the generality of modeling short sequences by constructing more learning objectives. Extensive experimental results show that SFKT achieves significant improvements over multiple benchmarks, demonstrating the value of exploring the modeling of sequences of excessive or insufficient lengths. Our code is available at https://github.com/zmy-9/SFKT.
FFF: Fragments-Guided Flexible Fitting for Building Complete Protein Structures

Cryo-electron microscopy (cryo-EM) is a technique for reconstructing the 3-dimensional (3D) structure of biomolecules (especially large protein complexes and molecular assemblies). As the resolution increases to the near-atomic scale, building protein structures de novo from cryo-EM maps becomes possible. Recently, recognition-based de novo building methods have shown the potential to streamline this process. However, it cannot build a complete structure due to the low signal-to-noise ratio (SNR) problem. At the same time, AlphaFold has led to a great breakthrough in predicting protein structures. This has inspired us to combine fragment recognition and structure prediction methods to build a complete structure. In this paper, we propose a new method named FFF that bridges protein structure prediction and protein structure recognition with flexible fitting. First, a multi-level recognition network is used to capture various structural features from the input 3D cryo-EM map. Next, protein structural fragments are generated using pseudo peptide vectors and a protein sequence alignment method based on these extracted features. Finally, a complete structural model is constructed using the predicted protein fragments via flexible fitting. Based on our benchmark tests, FFF outperforms the baseline methods for building complete protein structures.
High-mass X-ray Binaries

Binary systems in which a neutron star or black hole accretes material from a high-mass star are known as high-mass X-ray binaries (HMXBs). This chapter provides a brief introduction to the physics of wind accretion and an observational view of HMXBs, including their classification, X-ray spectra, X-ray variability, orbital and compact object properties, as well as studies of Galactic and Magellanic HMXB populations. Two classes of X-ray sources whose possible connections to HMXBs have been debated, ultraluminous X-ray sources and gamma-ray binaries, are also discussed. Approximately 300 HMXBs residing either in the Milky Way or the Magellanic Clouds have been discovered. The majority of these HMXBs host wind-accreting neutron stars. Their X-ray properties depend both on the interaction of the accreting material with the neutron star's strong magnetic field and the properties of the donor star's wind. Most HMXBs are classified as either supergiant XBs or Be XBs based on the spectral type of the donor star; these classes exhibit different patterns of X-ray variability and occupy different phase space in diagrams of neutron star spin versus orbital period. While studies of HMXBs in the Milky Way and Magellanic Clouds find that their luminosity functions have similar shapes, an overabundance of Be XBs in the Small Magellanic Cloud points to important variations of the HMXB population with metallicity and age.
Creating Android Malware Knowledge Graph Based on a Malware Ontology

As mobile and smart connectivity continue to grow, malware presents a permanently evolving threat to different types of critical domains such as health, logistics, banking, and community segments. Different types of malware have dynamic behaviors and complicated characteristics that are shared among members of the same malware family. Malware threat intelligence reports play a crucial role in describing and documenting the detected malware, providing a wealth of information regarding its attributes, patterns, and behaviors. There is a large amount of intelligent threat information regarding malware. The ontology allows the systematic organization and categorization of this information to ensure consistency in representing concepts and entities across various sources. In this study, we reviewed and extended an existing malware ontology to cover Android malware. Our extended ontology is called AndMalOnt. It consisted of 13 new classes, 16 object properties, and 31 data properties. Second, we created an Android malware knowledge graph by extracting reports from the MalwareBazaar repository and representing them in AndMalOnt. This involved generating a knowledge graph that encompasses over 2600 malware samples. Our ontology, knowledge graph, and source code are all open-source and accessible via GitHub
Radiation Produced with Slow-Wave Fundamental Mode and Generalized Fundamental mode in Periodic Structures

This study suggests an idea that radiation in a periodic leaky-wave antenna (PLWA) should be considered to be produced with the fundamental mode, regardless of whether it is fast-wave or slow-wave. The idea is different from the conventional PLWA theory, which considers it a fact that a PLWA produces radiation with its fast-wave space harmonic when the fundamental mode is slow-wave. To elaborate the idea, it is proved that there is not an eigen-equation like Pythagorean theorem for the fundamental mode in PLWAs. Then a non-uniform structure antenna is designed to show that slow-wave modes can produce leaky-wave radiation. Again it is proved that the difference of the phase constants between a slow-wave fundamental mode and its fast-wave space harmonics has not any effect on the radiation pattern of a PLWA. Moreover, it is clarified that the fundamental mode has a more definite physical significance than space harmonics. Finally, a concept of generalized fundamental modes is proposed without using Fourier expansion. The generalized fundamental modes have the same phase and attenuation constants as any space harmonics, and have physical significance as the conventional fundamental mode. Therefore, it could replace the roles that the space harmonics used to play.
Tourist-historic city.

Part 1 Introduction: the city between two futures the dimensions of the tourist-historic city conceptual scope and structure global scope and selection. Part 2 The historic city: the rise of the urban conservation movement motivations and justifications the concept of the historic city a development model. Part 3 The tourist city: tourism in cities tourism in the historic city the historic city as an urban tourism resource the resort city modelling the tourist city. Part 4 Modelling the tourist-historic city: the nature and use of a model establishing the model variations from the model limitations of the model. Part 5 Uses and users of the tourist-historic city: cohabitation and coincidence the tourist-historic city as a location for urban functions coexisting functions of the tourist-historic city the users of the tourist-historic city. Part 6 The planning, management and marketing of the tourist-historic city: the inevitability of management types of planning and management classifying tourist-historic cities. Part 7 The management of mono-functional tourist-historic cities: resource-based historic "gem" cities demand-based tourist cities the tourist-historic city in the tourist resort region retrospect. Part 8 The management of tourist-historic elements in large multifunctional cities: the big league tourist-historic cities the second division the large multifunctional city - convergence. Part 9 The management of tourist-historic elements in medium sized multifunctional cities: general characteristics urban revitalization - socio-economic motivations and the tourist-historic city the medium sized multifunctional city - a synthesis. Part 10 Conclusions: values, contentious issues and the present perspective conclusions for conservation conclusions for tourism conclusions for the city.
EFFECT OF CHANNEL MEANDERS ON FLOOD STAGE IN VALLEY

Results of this study indicate that for a meandering channel in a valley there is an interaction between the channel flow and valley flow. The nature of the interaction varies with stage, in that channel flow remains dominant when the overbank flow is relatively shallow, but may become insignificant when the overbank flow is deep. Once the valley flow becomes dominant, the presence of the meandering channel can actually produce greater stages than would occur if the channel were absent. The tests showed that the method recommended for straight channels with irregular cross sections applies with good accuracy, but that it would be totally erroneous to apply this method to a meandering channel in a valley. Although not tested, there is little doubt that the effects noted for a sinusoidal channel would be even more pronounced for a channel with a convoluted meander pattern.
KAI2 Can Do: Karrikin Receptor Function in Plant Development and Response to Abiotic and Biotic Factors

Abstract The α/β hydrolase KARRIKIN INSENSITIVE 2 (KAI2) functions as a receptor for a yet undiscovered phytohormone, provisionally termed KAI2 ligand (KL). In addition, it perceives karrikin, a butenolide compound found in the smoke of burnt plant material. KAI2-mediated signaling is involved in regulating seed germination and in shaping seedling and adult plant morphology, both above and below ground. It also governs responses to various abiotic stimuli and stresses and shapes biotic interactions. KAI2-mediated signaling is being linked to an elaborate cross-talk with other phytohormone pathways such as auxin, gibberellin, abscisic acid, ethylene and salicylic acid signaling, in addition to light and nutrient starvation signaling. Further connections will likely be revealed in the future. This article summarizes recent advances in unraveling the function of KAI2-mediated signaling and its interaction with other signaling pathways.
A semimechanistic pharmacokinetic/pharmacodynamic model for alanine aminotransferase‐based hepatotoxicity of methotrexate in paediatric patients with acute lymphoid leukaemia

Methotrexate (MTX) is recognized for its potential to induce hepatotoxicity, commonly manifested by elevated alanine aminotransferase (ALT) levels. However, the quantitative relationship between the pharmacokinetics (PK) of MTX and ALT‐based hepatotoxicity remains unclear. This study aimed to develop a semimechanistic PK/pharmacodynamic (PD) model to characterize the MTX‐induced hepatotoxicity based on ALT in paediatric patients with acute lymphoid leukaemia.
Wireless data transmission in a 560-GHz band using low-phase-noise terahertz wave generated by photomixing of a pair of distributed feedback lasers injection-locking to Kerr micro-resonator soliton comb

The demand for higher data rates in next-generation mobile wireless communication systems (6G) has led to significant interest in terahertz (THz) waves as a high-frequency, broad modulation bandwidth carrier wave. In this study, we propose and demonstrate a wireless data transfer in the 560-GHz band using low-phase-noise THz waves generated by photomixing of a pair of distributed feedback lasers injection-locking to Kerr micro-resonator soliton comb. Experimental results showed near-error-free on-off keying (OOK) data transfer at 1 Gbit/s in the 560-GHz band, with a Q-factor of 6.23, surpassing the error-free limit. Also, modulation formats of binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) were successfully used, showing clear constellation diagrams and relatively low root mean squared error vector magnitude (rms EVM) values of 23.9% and 23.6%, respectively. Moreover, data transfer at 0.4 Gbit/s in 16 quadrature amplitude modulation (16QAM) demonstrated clear isolated symbols and achieved a low rms EVM value of 8.1%, complying with the IEEE 802.15. 3d standard amendment. These demonstrations highlight the potential of using injection-locked DFB lasers with the Kerr micro-resonator soliton comb to achieve high-quality, high-speed wireless data transfer in the 560-GHz band. These findings contribute significantly to the advancement of wireless communication technology in the THz frequency range and pave the way for the realization of 6G wireless communication systems.
Towards Safe Multi-Level Human-Robot Interaction in Industrial Tasks

Multiple levels of safety measures are required by multiple interaction modes which collaborative robots need to perform industrial tasks with human co-workers. We develop three independent modules to account for safety in different types of human-robot interaction: vision-based safety monitoring pauses robot when human is present in a shared space; contact-based safety monitoring pauses robot when unexpected contact happens between human and robot; hierarchical intention tracking keeps robot in a safe distance from human when human and robot work independently, and switches robot to compliant mode when human intends to guide robot. We discuss the prospect of future research in development and integration of multi-level safety modules. We focus on how to provide safety guarantees for collaborative robot solutions with human behavior modeling.
Seed or soil: tracing back the plant mycobiota primary sources

Plants host diverse communities of fungi (collectively called the mycobiota) which play crucial roles in their development. The assembly processes of the mycobiota, however, remain poorly understood, in particular, whether it is transmitted by parents through the seeds (vertical transmission) or recruited in the environment (horizontal transmission). Here we attempt to quantify the relative contributions of horizontal and vertical transmission in the mycobiota assembly of a desert shrub, Haloxylon salicornicum, by comparing the mycobiota of in situ bulk soil and seeds to that of (i) in situ adult individuals and (ii) in vitro-germinated seedlings in soil collected in situ, either autoclaved or not. We show that the mycobiota is partially transmitted through the seeds to seedlings. In contrast, root mycobiota of adults are highly similar to that of bulk soil, whereas adult leaf mycobiota remain similar to that of seeds. Thus, the mycobiota is transmitted both horizontally and vertically depending on the plant tissue. Despite discrepancies between in situ and in vitro approaches, our result may also suggest a compositional turnover in plant mycobiota during plant development. Understanding the respective contribution of these transmission paths to the plant mycobiota is fundamental to deciphering potential coevolutionary processes between plants and fungi.
Spatialyze: A Geospatial Video Analytics System with Spatial-Aware Optimizations

Videos that are shot using commodity hardware such as phones and surveillance cameras record various metadata such as time and location. We encounter such geospatial videos on a daily basis and such videos have been growing in volume significantly. Yet, we do not have data management systems that allow users to interact with such data effectively. In this paper, we describe Spatialyze, a new framework for end-to-end querying of geospatial videos. Spatialyze comes with a domain-specific language where users can construct geospatial video analytic workflows using a 3-step, declarative, build-filter-observe paradigm. Internally, Spatialyze leverages the declarative nature of such workflows, the temporal-spatial metadata stored with videos, and physical behavior of real-world objects to optimize the execution of workflows. Our results using real-world videos and workflows show that Spatialyze can reduce execution time by up to 5.3x, while maintaining up to 97.1% accuracy compared to unoptimized execution.
Clinical manifestations and early effectiveness of methimazole in patients with graves’ hyperthyroidism-related severe hepatic dysfunction

Abstract Background Graves’ hyperthyroidism (GH) is often accompanied by mild to moderate liver injury, but severe hepatic dysfunction (SHD) is relatively rare. Whether patients with GH-related SHD can be treated with methimazole (MMI) remains controversial. This study aimed to determine the clinical characteristics and to evaluate the role of low-dose MMI for such patients. Methods 33 patients with GH-related SHD were selected for this retrospective study in the Fifth Medical Center of Chinese PLA General Hospital from January 2017 to July 2022. The clinical manifestations, therapeutic responses, and effectiveness of MMI were evaluated. Results Systemic jaundice (100.0%), yellow urine (100.0%), fatigue (87.9%), and goiter (66.7%) were the main symptoms. Total bilirubin (TBIL) had no linear correlation with free triiodothyronine (FT3) (r = −0.023, p = .899), free thyroxine (FT4) (r = 0.111, p = .540), T3 (r = −0.144, p = .425), and T4 (r = 0.037, p = .837). On the 14th day after admission, FT3, FT4, T3, T4, TBIL, direct bilirubin (DBIL), alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), γ-glutamyltransferase (GGT), and international normalized ratio (INR) decreased compared with the baseline (p < .05). The decrease rates of FT3, FT4, T3, T4, TBIL, and DBIL in the MMI group were higher than those in the non-MMI group (p < .05). The improvement rate of the MMI group (77.8%) was higher than that of the non-MMI group (9.5%, p = .001). MMI treatment is an independent predictor affecting the early improvement of patients (OR = 0.022, p = .010). Conclusions The main clinical manifestations of patients with GH-related SHD were symptoms related to liver disease. Low-dose MMI was safe and effective for them.
A Brain‐To‐Brain Mechanism for Social Transmission of Threat Learning

Survival and adaptation in environments require swift and efficacious learning about what is dangerous. Across species, much of such threat learning is acquired socially, e.g., through the observation of others’ (“demonstrators’”) defensive behaviors. However, the specific neural mechanisms responsible for the integration of information shared between demonstrators and observers remain largely unknown. This dearth of knowledge is addressed by performing magnetoencephalography (MEG) neuroimaging in demonstrator‐observer dyads. A set of stimuli are first shown to a demonstrator whose defensive responses are filmed and later presented to an observer, while neuronal activity is recorded sequentially from both individuals who never interacted directly. These results show that brain‐to‐brain coupling (BtBC) in the fronto‐limbic circuit (including insula, ventromedial, and dorsolateral prefrontal cortex) within demonstrator‐observer dyads predict subsequent expressions of learning in the observer. Importantly, the predictive power of BtBC magnifies when a threat is imminent to the demonstrator. Furthermore, BtBC depends on how observers perceive their social status relative to the demonstrator, likely driven by shared attention and emotion, as bolstered by dyadic pupillary coupling. Taken together, this study describes a brain‐to‐brain mechanism for social threat learning, involving BtBC, which reflects social relationships and predicts adaptive, learned behaviors.
Verfahren zur Genauigkeitsanalyse fuer Altkarten (Process on the Precision Analysis for Old Maps)

Abstract : The dissertation pronounces its aim to be the establishment of a basis for continual and optimized solution processes on the precision analysis of old maps, which are defined as "printed maps from the end of the 15th to the end of the 18 century" (3), with the following restrictions: 1) the realization of such a basis is purely by calculation, not manual, that is accessible as a normal, commercially available map plan might be; 2) only non-mobile points of reference have been taken into account, whereas changing parameters, such as coastlines, are not included; 3) only the old map in question is used, but measurements taken during that time period and their potential influence on the precision of the data do not configure in the study.
TemporalFED: Detecting Cyberattacks in Industrial Time-Series Data Using Decentralized Federated Learning

Industry 4.0 has brought numerous advantages, such as increasing productivity through automation. However, it also presents major cybersecurity issues such as cyberattacks affecting industrial processes. Federated Learning (FL) combined with time-series analysis is a promising cyberattack detection mechanism proposed in the literature. However, the fact of having a single point of failure and network bottleneck are critical challenges that need to be tackled. Thus, this article explores the benefits of the Decentralized Federated Learning (DFL) in terms of cyberattack detection and resource consumption. The work presents TemporalFED, a software module for detecting anomalies in industrial environments using FL paradigms and time series. TemporalFED incorporates three components: Time Series Conversion, Feature Engineering, and Time Series Stationary Conversion. To evaluate TemporalFED, it was deployed on Fedstellar, a DFL framework. Then, a pool of experiments measured the detection performance and resource consumption in a chemical gas industrial environment with different time-series configurations, FL paradigms, and topologies. The results showcase the superiority of the configuration utilizing DFL and Semi-Decentralized Federated Learning (SDFL) paradigms, along with a fully connected topology, which achieved the best performance in anomaly detection. Regarding resource consumption, the configuration without feature engineering employed less bandwidth, CPU, and RAM than other configurations.
Fire and Explosions in Avatar: The Way of Water

Combustion workflows for the Avatar sequel(s) were built from the ground up, aiming at physical plausibility and predictability, facilitated by careful modeling from molecular-level chemical reactions to large-scale thermodynamics. Onset references for torches, flame bars, and burning Marui villages guided development work across simulation, look development, and rendering. Using chemical formulas and properties of real-world fuels, and tuning pre-mixing with oxygen, allowed faithfully capturing a number of desirable effects, such as “oxygen starvation” and flickering of thin flames, without the need for additional artistic variables. Using our new solver created a consistent look across sequences at different scales, allowing artists to replace library fires with hero solves when interaction or a particular behavior was required.