Miracle-dz/UniFAR-FTUs huggingface dataset:
The LSST Era of Supermassive Black Hole Accretion Disk Reverberation Mapping

The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) will detect an unprecedentedly large sample of actively accreting supermassive black holes with typical accretion disk (AD) sizes of a few light days. This brings us to face challenges in the reverberation mapping (RM) measurement of AD sizes in active galactic nuclei using interband continuum delays. We examine the effect of LSST cadence strategies on AD RM using our metric AGN_TimeLagMetric. It accounts for redshift, cadence, the magnitude limit, and magnitude corrections for dust extinction. Running our metric on different LSST cadence strategies, we produce an atlas of the performance estimations for LSST photometric RM measurements. We provide an upper limit on the estimated number of quasars for which the AD time lag can be computed within 0 < z < 7 using the features of our metric. We forecast that the total counts of such objects will increase as the mean sampling rate of the survey decreases. The AD time lag measurements are expected for >1000 sources in each deep drilling field (DDF; (10 deg2)) in any filter, with the redshift distribution of these sources peaking at z ≈ 1. We find the LSST observation strategies with a good cadence (≲5 days) and a long cumulative season (∼9 yr), as proposed for LSST DDF, are favored for the AD size measurement. We create synthetic LSST light curves for the most suitable DDF cadences and determine RM time lags to demonstrate the impact of the best cadences based on the proposed metric.
Low Emission Building Control with Zero-Shot Reinforcement Learning

Heating and cooling systems in buildings account for 31% of global energy use, much of which are regulated by Rule Based Controllers (RBCs) that neither maximise energy efficiency nor minimise emissions by interacting optimally with the grid. Control via Reinforcement Learning (RL) has been shown to significantly improve building energy efficiency, but existing solutions require access to building-specific simulators or data that cannot be expected for every building in the world. In response, we show it is possible to obtain emission-reducing policies without such knowledge a priori–a paradigm we call zero-shot building control. We combine ideas from system identification and model-based RL to create PEARL (Probabilistic Emission-Abating Reinforcement Learning) and show that a short period of active exploration is all that is required to build a performant model. In experiments across three varied building energy simulations, we show PEARL outperforms an existing RBC once, and popular RL baselines in all cases, reducing building emissions by as much as 31% whilst maintaining thermal comfort. Our source code is available online via: https://enjeeneer.io/projects/pearl/.
Acoustically levitated lock and key grains

We present a scheme for generating shape-dependent, specific bonds between millimeter scale particles, using acoustic levitation. We levitate particles in an ultrasonic standing wave, allowing for substrate-free assembly. Secondary scattering generates shape-dependent attractive forces between particles, while driving the acoustic trap above its resonance frequency produces active fluctuations that mimic an effective temperature. We 3D print planar particles, and show that the local curvature of their binding sites controls the selectivity for attaching a matching particle. We find that the bound-state probability and bound-state lifetime can be independently tuned via the binding site depth and height respectively. Finally, we show that these principles can be used to design particles that assemble into complex structures.
Van der Waals Materials for Applications in Nanophotonics

Numerous optical phenomena and applications have been enabled by nanophotonic structures. Their current fabrication from high refractive index dielectrics, such as silicon (Si) or gallium phosphide (GaP), pose restricting fabrication challenges while metals, relying on plasmons and thus exhibiting high ohmic losses, limit the achievable applications. An emerging class of layered, so‐called van der Waals (vdW), crystals is presented as a viable nanophotonics platform in this work. The dielectric response of 11 mechanically exfoliated thin‐film (20–200 nm) vdW crystals is extracted, revealing high refractive indices up to n = 5, pronounced birefringence up to Δn = 3, sharp absorption resonances, and a range of transparency windows from ultraviolet to near‐infrared. Nanoantennas are subsequently fabricated on silicon dioxide (SiO2) and gold, utilizing the compatibility of vdW thin films with a variety of substrates. Pronounced Mie resonances are observed due to the high refractive index contrast on SiO2, leading to a strong exciton‐photon coupling regime as well as largely unexplored high‐quality‐factor, hybrid Mie‐plasmon modes on gold. Additional vdW‐material‐specific degrees of freedom in fabrication are further demonstrated by realizing nanoantennas from stacked twisted crystalline thin‐films, enabling control of nonlinear optical properties, and post‐fabrication nanostructure transfer, important for nano‐optics with sensitive materials.
Anatomy-XNet: An Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification in Chest X-Rays

Thoracic disease detection from chest radiographs using deep learning methods has been an active area of research in the last decade. Most previous methods attempt to focus on the diseased organs of the image by identifying spatial regions responsible for significant contributions to the model's prediction. In contrast, expert radiologists first locate the prominent anatomical structures before determining if those regions are anomalous. Therefore, integrating anatomical knowledge within deep learning models could bring substantial improvement in automatic disease classification. Motivated by this, we propose Anatomy-XNet, an anatomy-aware attention-based thoracic disease classification network that prioritizes the spatial features guided by the pre-identified anatomy regions. We adopt a semi-supervised learning method by utilizing available small-scale organ-level annotations to locate the anatomy regions in large-scale datasets where the organ-level annotations are absent. The proposed Anatomy-XNet uses the pre-trained DenseNet-121 as the backbone network with two corresponding structured modules, the Anatomy Aware Attention (A3) and Probabilistic Weighted Average Pooling, in a cohesive framework for anatomical attention learning. We experimentally show that our proposed method sets a new state-of-the-art benchmark by achieving an AUC score of 85.78%, 92.07%, and, 84.04% on three publicly available large-scale CXR datasets–NIH, Stanford CheXpert, and MIMIC-CXR, respectively. This not only proves the efficacy of utilizing the anatomy segmentation knowledge to improve the thoracic disease classification but also demonstrates the generalizability of the proposed framework.
Weighted norm inequalities for maximal functions and singular integrals

A thoracic drainage device including a rigid container having a drainage collection chamber and a liquid seal chamber centered above the collection chamber. A tube adapted for connection with the pleural cavity of a patient is connected to the lid of the device and extends into the liquid seal chamber to a point below the level of an initial amount of liquid provided therein. The liquid seal chamber has a relatively small height relative to its length and width so that it contains a relatively large amount of liquid of shallow depth. The seal chamber has an upper wall with a central opening for the flow of liquid through the opening and into the collection chamber, the upper wall preventing or reducing the flow of liquid out of the liqud seal chamber due to an inadvertent tipping of the device or sloshing during movement from one location to another.
ON QUADRISECANT LINES OF THREEFOLDS IN P 5

We study smooth threefolds of P^5 whose quadrisecant lines don't fill up the space. We give a complete classification of those threefolds X whose only quadrisecant lines are the lines contained in X . Then we prove that, if X admits "true" quadrisecant lines, but they don't fill up P^5 , then either X is contained in a cubic hypersurface, or it contains a family of dimension at least two of plane curves of degree at least four.
The impulsive phase in solar flares: recent multi-wavelength results and their implications for microwave modeling and observations

This short paper reviews several recent key observations of the processes occurring in the lower atmosphere (chromosphere and photosphere) during flares. These are: evidence for compact and fragmentary structure in the flare chromosphere, the conditions in optical flare footpoints, step-like variations in the magnetic field during the flare impulsive phase, and hot, dense 'chromospheric' footpoints. The implications of these observations for microwaves are also discussed.
AC conductivity of V2O5-TeO2 glasses

The electrical conductivity and dielectric constant of V2O5-TeO2 glasses of compositions 10-80 mol% V2O5 have been measured in the frequency range 0.1-100 kHz and in the temperature range 77-400K. A frequency dependence according to the relation sigma ( omega )=A omega s has been observed, and values of the exponent s are less than unity (between 0.95 and 0.80 depending on the composition). The data of AC conductivity have been analysed in the light of different theoretical models based on quantum-mechanical tunnelling (QMT) and hopping over the barrier (HOB). The analysis shows that neither QMT nor HOB models can explain the data quantitatively. A linear dependence of the conductivity and a temperature-independent s at low temperatures, and a non-linear increase of conductivity at higher temperatures for higher frequencies agree respectively with QMT and HOB models. It is difficult to estimate the absolute value of tau 0 (characteristic relaxation time of the system) or to arrive at a definite conclusion about the conduction mechanism by the Butcher and Morys model (1973) owing to experimental uncertainties in the measured values epsilon '( omega ) and the lack of knowledge of epsilon infinity . A detailed investigation of epsilon ' as a function of composition for these glasses has been made. A non-linear variation of dielectric constant with concentration has been observed. The abnormally high dielectric constant ( approximately 30) of the low composition V2O5-TeO2 glasses may be attributed to the characteristic role played by the glass former, TeO2.
Triple‐threat quantitative multiplexed plasma proteomics analysis on immune complex disease MRL‐lpr mice

Systemic lupus erythematosus is a common autoimmune inflammatory disease which is associated with increases in autoantibodies and immune complexes that deposit in the kidney. The MRL‐lpr mouse is a common mouse model used for the study of lupus and immune complex glomerulonephritis but very little is known about the plasma proteome changes in this model. We performed in‐depth quantitative proteome profiling on MRL‐lpr and control (strain MpJ) mice to investigate the changes in the proteome, immunoglobulins and their glycoproteome as well as protein and immune complexes. Methodologies used included immunohistochemistry, immunoglobulin isotyping, multiplexed proteome profiling, immunoglobulin immunoprecipitation with glycoproteome profiling, and size exclusion chromatography (SEC) profiling to enable a comprehensive proteome profiling of proteins and protein complexes. We also used a novel native multiplexed plasma proteome profiling (NativeMP3) method that relies on native enrichment of plasma proteins enabling ultra‐deep single shot profiling where we identified 922 plasma proteins at 1% false discovery rate (FDR) in a single shot mass spectrometry run. We observed many large plasma protein differences between the MRL‐lpr and control strain including differences in the immunoglobulins, immunoglobulins against specific antigens, chemokines, and proteases as well as changes in protein complexes such as the immunoproteasome.
Human osteoprogenitor cells obtained from traumatic heterotopic ossification samples showed enhanced osteogenic differentiation potential and ERK/hedgehog signaling than that from normal bone

Traumatic heterotopic ossification (HO) refers to the abnormal ectopic osteogenesis following trauma, causing limb dysfunction and seriously lowering the life quality of patients. Aberrant osteogenic behavior of progenitor cells that ectopically accumulated within the soft tissues are believed to be responsible for HO formation. However, the detailed mechanism still remained to be clarified. Here in this study, we successfully isolated osteoprogenitors from human heterotopic ossification tissues (HO‐ops) and identified their stemness and multi‐directional differentiation potential. Using alkaline phosphatase staining together with alizarin red staining, we confirmed that the HO‐ops in the heterotopic ossified tissues gained greater osteogenic potential than the normal human bone marrow mesenchymal stem cells (HBMSCs). RT‐qPCR also indicated that HO‐ops obtained more gene transcriptions of critical osteogenic determinators than HBMSCs. In addition, through Western blot, we proved that ERK signaling pathway and hedgehog signaling pathway were significantly activated in the HO‐ops. When U0126 and cyclopamine were used to inhibit ERK signaling and hedgehog signaling respectively, the osteogenic potential of HO‐ops decreased significantly. The hedgehog signaling and ERK signaling also showed cross‐talk in HO‐ops during osteogenic differentiation in HO‐ops during osteogenic differentiation. The elevated ERK signaling and hedgehog signaling were further confirmed in the human traumatic HO sample sections by immunohistochemical staining. In sum, our results showed that the activation of ERK and hedgehog signaling pathway jointly enhanced the osteogenic potential of HO‐ops to induce the formation of traumatic HO, which provides novel insights into the molecular basis of HO formation and offers promising targets for future therapeutic strategy.
LETTER TO THE EDITOR: Anomalous low temperature states in CeNi2Ge2 and CePd2Si2

High purity samples of the paramagnetic 4f-electron metal CeNi2Ge2 exhibit a non-Fermi-liquid form of the resistivity Δρ~Tx with x<1.5 and decreasing towards 1 with increasing sample purity. Measurements of ρ versus T as a function of magnetic field and pressure show that this strange metallic phase is connected to the proximity of an antiferromagnetic quantum critical point as in the isoelectronic relative CePd2Si2 near 2.8 GPa. The anomalous power-law dependence is surprisingly stable over extended ranges in temperature and pressure and challenges current theory of magnetic quantum phase transitions.
Dropout Rate Prediction for MOOC based on Inceptiontime Model

As a representative Internet education model, MOOC has influenced the development process of education. The student dropout rate is an important indicator of MOOC, which is important for lecturers to improve course quality and teaching effectiveness. We predict student dropout rates based on a dataset provided by the Open University (OU)1 . We transformed the data provided by the OU into time series data based on the number of times students clicked on the course per day. For the time-series data properties, we propose an InceptionTime-based model for predicting MOOC dropout rate. Our proposed new model primarily uses multiple Inception modules connected via a residual network. Parallel operations are performed on our data using MaxPooling operation and three different lengths of convolution within the initial module. Extensive comparative experiments were conducted comparing our proposed model with Resnet and Time series forest models on educational data from multiple semesters. The experimental results show that our proposed model significantly outperforms the other two models.
Perceptions of Vietnamese Lecturers and Administrators on STEAM Competence and Developing Students’ Competences in STEAM Education

Interdisciplinary and transdisciplinary learning in schools has become a popular and rapidly rising subject of focus for educational reform across the world. This sparks discussion on STEAM (Science, Technology, Engineering, Arts, and Mathematics), which is changing educational paradigms by incorporating art into STEM (science, technology, engineering, and mathematics) subjects. Understanding the nature of STEAM correctly is one of the deciding factors to the success of STEAM implementation. Therefore, the main purpose of this study is to investigate how lecturers and administrators of an institution of higher education in Vietnam perceive STEAM education and its developing students’ competences. The qualitative data were collected from semi-structure interviews with 6 academics and managers from two campuses of this institution. The results show that they have positive perceptions towards STEAM education. Students enter college with a set of well-rounded skills that will assist them in adapting to a continuously changing and fast-paced workplace, regardless of the specific role or industry. STEAM combines important disciplines to create a welcoming learning environment that encourages all students to engage, contribute, and problem solve.
Effect of Different Types of Recycled Concrete Aggregates on Equivalent Concrete Strength and Drying Shrinkage Properties

Residual mortar attached to recycled concrete aggregate (RCA) always leads to a decrease in Young’s modulus and an increase in the drying shrinkage of RCA concrete, mainly due to an increase of total mortar volume. To overcome this inherent problem, the modified and equivalent mortar volume (EMV) methods were proposed by researchers. Despite the comparable test results, both models are still subject to the slump loss problem. Thus, under the same W/C (water to cement ratio) ratio and slump condition, this study assessed the influence of the modified EMV mix method on RCA concrete properties. A total of six mixes were proportioned using the modified EMV method with three different RCAs. Test results show that the concrete mixed with RCA produced from old PC concrete sleepers exhibited compressive strength, Young’s modulus, and flexural strength values within 2% variation, equivalent to those values of the companion natural aggregate concrete. In other mixes, compressive strength was found to decrease to 11–20%. It was observed that for 100% replacement of RCA mix, Young’s modulus increased to 10% and drying shrinkage increased to 8% only, while for 50% replacement of RCA mix, Young’s modulus decreased to 8% and drying shrinkage dropped to 4%.
Trauma is an exhausting platelet experience

Platelets are an essential part of the hemostatic process and tight regulation of platelet activity is key to maintaining normal hemo static function in the vessel. Platelet dysfunction is typically thought of as being associated with an increased risk for occlusive throm botic events leading to life- threatening pathophysiological condi tions such as myocardial infarction and stroke. Hallmarks of platelet hyperreactivity include (1) increased alpha granule secretion lead ing to P- selectin expression on the platelet surface, (2) increased dense granule secretion leading to an increase in the release of pro-thrombotic small molecules into the blood such as ADP, calcium, and 5- HT, and (3) increased inside- out activation of the integrin α IIb β 3 on the platelet surfaced resulting in platelet– platelet and platelet– extracellular matrix adhesion and inside- out activation of the plate let. platelets to minimize platelet reactivity through tar geting the various receptors and intracellular signaling increased bleeding due to incomplete clot formation, reduced clot strength, and/or thrombolysis. The
Ex vivo midgut cultures of Aedes aegypti are efficiently infected by mosquito-borne alpha- and flaviviruses

Aedes aegypti mosquitoes can transmit several arboviruses, including chikungunya virus (CHIKV), dengue virus (DENV), and Zika virus (ZIKV). When blood-feeding on a virus-infected human, the mosquito ingests the virus into the midgut (stomach), where it replicates and must overcome the midgut barrier to disseminate to other organs and ultimately be transmitted via the saliva. Current tools to study mosquito-borne viruses (MBVs) include 2D-cell culture systems and in vivo mosquito infection models, which offer great advantages, yet have some limitations. Here, we describe a long-term ex vivo culture of Ae. aegypti midguts. Cultured midguts were metabolically active for 7 days in a 96-well plate at 28°C and were permissive to ZIKV, DENV, Ross River virus (RRV) and CHIKV. Ex vivo midguts from Culex pipiens mosquitoes were found to be permissive to Usutu virus (USUV). Immunofluorescence staining confirmed viral protein synthesis in CHIKV-infected midguts of Ae. aegypti. Furthermore, fluorescence microscopy revealed replication and spread of a reporter DENV in specific regions of the midgut. In addition, two known antiviral molecules, β-D-N4-hydroxycytidine (NHC) and 7-deaza-2’-C-methyladenosine (7DMA), were able to inhibit CHIKV and ZIKV replication, respectively, in the ex vivo model. Together, our results show that ex vivo midguts can be efficiently infected with mosquito-borne alpha- and flaviviruses and employed to evaluate antiviral drugs. Furthermore, the setup can be extended to other mosquito species. Ex vivo midgut cultures could thus be a new model to study MBVs, offering the advantage of reduced biosafety measures compared to infecting living mosquitoes. Importance Mosquito-borne viruses (MBVs) are a significant global health threat since they can cause severe diseases in humans, such as hemorrhagic fever, encephalitis, and chronic arthritis. MBVs rely on the mosquito vector to infect new hosts and perpetuate virus transmission. No therapeutics are currently available. The study of arbovirus infection in the mosquito vector can greatly contribute to elucidating strategies for controlling arbovirus transmission. This work investigated the infection of midguts from Aedes aegypti mosquitoes in an ex vivo platform. We found several MBVs capable of replicating in the midgut tissue, including viruses of major health importance, such as dengue, chikungunya, and Zika viruses. Additionally, antiviral compounds reduced arbovirus infection in the cultured midgut tissue. Overall, the midgut model emerges as a useful tool for diverse applications such as studying tissue-specific responses to virus infection and screening potential anti-arboviral molecules.
Multi-channel deep learning with intracranial neurostimulation can localize seizure onset zones in humans

In drug resistant temporal lobe epilepsy, automated tools for seizure onset zone (SOZ) localization using brief interictal recordings would supplement presurgical evaluations and improve care. Thus, we sought to localize SOZs by training a multi-channel convolutional neural network on stereo-EEG (SEEG) cortico-cortical evoked potentials. We performed single pulse electrical stimulation with 10 drug resistant temporal lobe epilepsy patients implanted with SEEG. Using the 500,000 unique post-stimulation SEEG epochs, we trained a multi-channel one-dimensional convolutional neural network to determine whether an SOZ was stimulated. SOZs were classified with a mean leave-one-patient-out testing sensitivity of 78.1% and specificity of 74.6%. To achieve maximum accuracy, the model requires a 0-350 ms post stimulation time period. Post-hoc analysis revealed that the model accurately classified unilateral vs bilateral mesial temporal lobe seizure onset, and neocortical SOZs. This is the first demonstration, to our knowledge, that a deep learning framework can be used to accurately classify SOZs using cortico-cortical evoked potentials. Our findings suggest accurate classification of SOZs relies on a complex temporal evolution of evoked potentials within 350 ms of stimulation. Validation in a larger dataset could provide a practical clinical tool for the presurgical evaluation of drug resistant epilepsy.