Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning Based Cooperative Scheduling with Distributed Non-linear Predictive Coding for Small Spacecraft Swarms

A deep learning based non-linear predictive coding (NLPC) source compression and cognitive cooperative relay scheduling approach is developed for small-spacecraft swarms used in imaging based remote sensing missions. A LEO satellite swarm complemented by a number of earth stations and GEO satellite relays is specifically considered, although the developed approach is applicable for lunar and other planetary and space destinations as well. Each swarm node employs a recurrent convolutional neural network (RCNN) to predict its future observations based on immediate past observations and encodes the prediction error as its payload. A novel image reconstruction method that ensures maintaining an exact replica of the RCNN at the earth receiver without explicitly sharing the network weights is also proposed. Proposed cognitive cooperative relay scheduling algorithm also makes use of the same RCNN to predict future payload size based on which nodes are categorized as source and relay nodes. A multi-objective optimization algorithm is formulated that allows relay capacity allocation by taking into account various desired performance objectives and priority handling. Simulation results verify that the proposed NLPC and cooperative scheduling can significantly increase the amount of image data delivered to the earth while also drastically cutting down image delay and improving fairness among data delivered from each satellite node.
Glacial‐Isostatic Adjustment Models Using Geodynamically Constrained 3D Earth Structures

Glacial‐isostatic adjustment (GIA) is the key process controlling relative sea‐level (RSL) and paleo‐topography. The viscoelastic response of the solid Earth is controlled by its viscosity structure. Therefore, the appropriate choice of Earth structure for GIA models is still an important area of research in geodynamics. We construct 18 3D Earth structures that are derived from seismic tomography models and are geodynamically constrained. We consider uncertainties in 3D viscosity structures that arise from variations in the conversion from seismic velocity to temperature variations (factor r) and radial viscosity profiles (RVP). We apply these Earth models to a 3D GIA model, VILMA, to investigate the influence of such structure on RSL predictions. The variabilities in 3D Earth structures and RSL predictions are investigated for globally distributed sites and applied for comparisons with regional 1D models for ice center (North America, Antarctica) and peripheral regions (Central Oregon Coast, San Jorge Gulf). The results from 1D and 3D models reveal substantial influence of lateral viscosity variations on RSL. Depending on time and location, the influence of factor r and/or RVP can be reverse, for example, the same RVP causes lowest RSL in Churchill and largest RSL in Oregon. Regional 1D models representing the structure beneath the ice and 3D models show similar influence of factor r and RVP on RSL prediction. This is not the case for regional 1D models representing the structure beneath peripheral regions indicating the dependence on the 3D Earth structure. The 3D Earth structures of this study are made available.
Ocean biogeochemistry in the Canadian Earth System Model version 5.0.3: CanESM5 and CanESM5-CanOE

Abstract. The ocean biogeochemistry components of the Canadian Earth System Model v. 5 are presented and compared to observations and other models. CanESM5 employs the same biogeochemistry module as CanESM2 whereas CanESM5-CanOE (“Canadian Ocean Ecosystem model”) is a new, more complex biogeochemistry module developed for Sixth Coupled Model Intercomparison Project (CMIP6), with multiple food chains, flexible phytoplankton elemental ratios, and a prognostic iron cycle. This new model is described in detail and the outputs compared to CanESM5 and CanESM2, as well as to observations and other CMIP6 models. Both CanESM5 models show gains in skill relative to CanESM2, which are attributed primarily to improvements in ocean circulation. CanESM5-CanOE shows improved skill relative to CanESM5 in some areas. CanESM5-CanOE includes a prognostic iron cycle, and maintains high nutrient / low chlorophyll conditions in the expected regions (in CanESM2 and CanESM5, iron limitation is specified as a temporally static ‘mask’). Surface nitrate concentrations are biased low in the subarctic Pacific and equatorial Pacific, and high in the Southern Ocean. Export production in CanESM5-CanOE is among the lowest for CMIP6 models; in CanESM5 it is among the highest, but shows the most rapid decline after about 1980. CanESM5-CanOE has relatively low concentrations of zooplankton and detritus relative to phytoplankton, and a high and relatively constant living phytoplankton fraction of total particulate organic matter. In most regions, large and small phytoplankton show decoupled seasonal cycles with greater abundance of large phytoplankton in the productive seasons. Cumulative ocean uptake of anthropogenic carbon dioxide through 2014 is lower in both CanESM5 models than in observation-based estimates or the model ensemble mean, and is lower in CanESM5-CanOE (122 PgC) than in CanESM5 (132 PgC).
A Drift-Resilient Hardware Implementation of Neural Accelerators Based on Phase Change Memory Devices

Memory devices, such as the phase change memory (PCM), have recently shown significant breakthroughs in terms of compactness, 3-D stacking capability, and speed up for deep learning neural accelerators. However, PCM is affected by the conductance drift, which prevents a precise definition of the synaptic weights in artificial neural networks. Here, we propose an efficient system-level methodology to develop drift-resilient multilayer perceptron (MLP) networks. The procedure guarantees high testing accuracy under conductance drift of the devices and enables the use of only positive weights. We validate the methodology using MNIST, rand-MNIST, and Fashion-MNIST datasets, thus offering a roadmap for the implementation of integrated nonvolatile memory-based neural networks. We finally analyze the proposed architecture in terms of throughput and energy efficiency. This work highlights the relevance of robust PCM-based design of neural networks for improving the computational capability and optimizing energetic efficiency.
Bayesian Inference for Time Delay Systems with Application to Connected Automated Vehicles

In this paper, a Bayesian inference problem is set up to infer the time delay and the resistance models from the dynamics of a connected automated vehicle. The delayed rejection adaptive Metropolis Markov chain Monte Carlo method is applied to obtain the posterior distributions of time delay and resistance parameters simultaneously using experimental data. The estimations of the time delay are shown to be consistent among multiple datasets and different resistance models. The distribution of the posterior indicates that there exist multiple modes in time delay, corresponding to different behaviors in acceleration and deceleration.
Response of rice-mycorrhizal association to arsenate exposure

Rice-mycorrhizal association helps the plants inphosphate acquisition and improves stress tolerance.The aim of present study was to analyse the impactof arsenic (As) - stress on mycorrhiza colonized (Co)and non-colonized (NCo) rice plants with respect to antioxidantmechanism. The rice seedlings were growninitially under control conditions for 45 d for establishmentof mycorrhizal association. The Co and NCoplants were then subjected to 12.5 ¹M arsenate [As(V)]exposure for 1 d and 3 d in hydroponics. The Coplants showed significant stimulation in activities ofvarious antioxidant enzymes viz., superoxide dismutase(SOD), guaiacol peroxidase (GPX), catalase (CAT) andglutathione reductase (GR) in both root and shoot uponAs(V) exposure as compared to that of NCo plants. Consequently,a notable increase in the photosynthetic pigmentsand decrease in H2O2 level and lipid peroxidationwasobserved in Co plants subjected to As(V) stressin comparison to that of NCo plants. Hence, myccorhizalsymbiosis was found to be effective in impartingtolerance to As stress and could serve as a potentialstrategy to mitigate As toxicity in rice in future.
Eccentric Dipole Evolution during the Last Reversal, Last Excursions, and Holocene Anomalies. Interpretation Using a 360-Dipole Ring Model

The eccentric dipole (ED) is the next approach of the geomagnetic field after the generally used geocentric dipole. Here, we analyzed the evolution of the ED during extreme events, such as the Matuyama-Brunhes polarity transition (~780 ka), the Laschamp (~41 ka) and Mono Lake (~34 ka) excursions, and during the time of two anomalous features of the geomagnetic field observed during the Holocene: the Levantine Iron Age Anomaly (LIAA, ~1000 BC) and the South Atlantic Anomaly (SAA, analyzed from ~700 AD to present day). The analysis was carried out using the paleoreconstructions that cover the time of the mentioned events (IMMAB4, IMOLEe, LSMOD.2, SHAWQ-Iron Age, and SHAWQ2k). We found that the ED moves around the meridian plane of 0–180° during the reversal and the excursions; it moves towards the region of the LIAA; and it moves away from the SAA. To investigate what information can be extracted from its evolution, we designed a simple model based on 360-point dipoles evenly distributed in a ring close to the inner core boundary that can be reversed and their magnitude changed. We tried to reproduce with our simple model the observed evolution of the ED, and the total field energy at the Earth’s surface. We observed that the modeled ED moves away from the region where we set the dipoles to reverse. If we consider that the ring dipoles could be related to convective columns in the outer core of the Earth, our simple model would indicate the potential of the displacement of the ED to give information about the regions in the outer core where changes start for polarity transitions and for the generation of important anomalies of the geomagnetic field. According to our simple model, the regions in which the most important events of the Holocene occur, or in which the last polarity reversal or excursion begin, are related to the regions of the Core Mantle Boundary (CMB), where the heat flux is low.
Casting a Wide Net: The Value of Collaboration and Outreach with Source Communities in the Analysis of Historic Native American Fishing Nets

Abstract The Lenape Tribe of Delaware is one of two recognized tribes within the state of Delaware. Having only gained state recognition in 2016, the group is actively working to regain the lifeways of their ancestors that have been lost in the aftermath of colonization and systemic oppression. This paper discusses collaborative research between the author, a student in Art Conservation, and the Lenape Tribe of Delaware on the once-crucial practice of net-tying. It addresses the impetus for the project and its role in object-based decolonization and Indigenous knowledge reclamation. The research was inspired by the last known Lenape netmaker, Clem Carney, whose work was collected by anthropologists in the early 1900s but since forgotten. The project was completed in collaboration with the Tribe from initial proposal onward and included three main stages: examination of fishing nets from Native Mid-Atlantic groups at the National Museum of the American Indian and the American Museum of Natural History; the compilation of an inventory of Native Mid-Atlantic nets and associated tools from institutions throughout North America; and outreach. Outreach efforts included a Tribal Delegation to the National Museum of the American Indian Cultural Resources Center, presentations to both the Native and non-Native community, and net-making workshops held at the Biggs Museum of American Art in Dover, DE. Through these events and a range of media posts and articles, it is estimated that 7,000 people learned about this collaboration. The project has prompted subsequent collaborations and serves as a model for community-driven research.
A Review of Advanced Impedance Biosensors with Microfluidic Chips for Single-Cell Analysis

Electrical impedance biosensors combined with microfluidic devices can be used to analyze fundamental biological processes for high-throughput analysis at the single-cell scale. These specialized analytical tools can determine the effectiveness and toxicity of drugs with high sensitivity and demonstrate biological functions on a single-cell scale. Because the various parameters of the cells can be measured depending on methods of single-cell trapping, technological development ultimately determine the efficiency and performance of the sensors. Identifying the latest trends in single-cell trapping technologies afford opportunities such as new structural design and combination with other technologies. This will lead to more advanced applications towards improving measurement sensitivity to the desired target. In this review, we examined the basic principles of impedance sensors and their applications in various biological fields. In the next step, we introduced the latest trend of microfluidic chip technology for trapping single cells and summarized the important findings on the characteristics of single cells in impedance biosensor systems that successfully trapped single cells. This is expected to be used as a leading technology in cell biology, pathology, and pharmacological fields, promoting the further understanding of complex functions and mechanisms within individual cells with numerous data sampling and accurate analysis capabilities.
Pengaruh Proses Pemutihan Multi Tahap Serat Selulosa Dari Limbah Tandan Kosong Kelapa Sawit

Penelitian ini bertujuan untuk meningkatkan kandungan selulosa limbah tandan kosong kelapa sawit melalui proses bertahap delignifikasi NaOH dilanjutkan dengan pemutihan menggunakan NaClO 2 . Hasil penelitian menunjukkan bahwa kandungan selulosa limbah tandan kosong kelapa sawit berhasil ditingkatkan hingga hampir dua kali dari 37,6 ± 0,3% menjadi 84,2 ± 0,3%. Lebih lanjut, proses pemutihan multi tahap menggunakan NaClO 2 dapat menurunkan kandungan lignin tandan kosong kelapa sawit menjadi sebesar 3,1 ± 0,2% hampir sama dengan standar selulosa, yaitu 2,6%. Penggunaan NaClO 2 juga mampu menurunkan kadar hemiselulosa hingga 12,6%, lebih rendah dibandingkan standar selulosa, yaitu 16,6%. Dari hasil FTIR , gugus puncak serapan selulosa meningkat secara signifikan, sedangkan hemiselulosa dan lignin mengalami penurunan intensitas. Analisa SEM menunjukkan bahwa proses delignifikasi basa dan pemutihan menyebabkan permukaan serat TKS berpori dan bersih yang mengindikasikan berkurangnya lignin dan hemiselulosa. Berdasarkan hasil penelitian ini, proses delignifikasi NaOH dan pemutihan NaClO 2 memiliki selektivitas tinggi yang dapat secara simultan mengurangi kadar hemiselulosa dan lignin tanpa merusak struktur selulosa.
Charge Transfer Complexes of 1,3,6-Trinitro-9,10-phenanthrenequinone with Polycyclic Aromatic Compounds

Understanding the interactions of organic donor and acceptor molecules in binary associates is crucial for design and control of their functions. Herein, we carried out a theoretical study on the properties of charge transfer complexes of 1,3,6-trinitro-9,10-phenanthrenequinone (PQ) with 23 aromatic π-electron donors. Density functional theory (DFT) was employed to obtain geometries, frontier orbital energy levels and amounts of charge transfer in the ground and first excited states. For the most effective donors, namely, dibenzotetrathiafulvalene, pentacene, tetrathiafulvalene, 5,10-dimethylphenazine, and tetramethyl-p-phenylenediamine, the amount of charge transfer in the ground state was shown to be 0.134−0.240 e−. Further, a novel charge transfer complex of PQ with anthracene was isolated in crystalline form and its molecular and crystal structure elucidated by single-crystal synchrotron X-ray diffraction.
Optoelectronic Synapse Based on IGZO‐Alkylated Graphene Oxide Hybrid Structure

Recently, research interest in brain‐inspired neuromorphic computing based on robust and intelligent artificial neural networks has surged owing to the ability of such technology to facilitate massive parallel, low‐power, highly adaptive, and event‐driven computing. Here, a photosynaptic device with a novel weight updating mechanism for high‐speed and low‐power optoelectronic spike processing is proposed, wherein a synaptic weight is controlled by a mixed spike consisting of voltage and light spikes; the light spike, in particular, boosts up the probability of electron detrapping from graphene oxide charge‐trapping layer to the photosensitive indium–gallium–zinc oxide charge‐transporting layer. Compared to electrically operating synaptic device, the magnitude of conductance change in the proposed photosynaptic device increases remarkably from 2.32 to 5.95 nS without degradation of the nonlinearity (potentiation/depression values are changed from 4.24/8 to 5/8). Owing to this enhancement of synaptic operation, the recognition rates for the Modified National Institute of Standards and Technology digit patterns improve from 36% and 49% to 50% and 62% in artificial neural networks using long‐term potentiation/depression characteristics with 20 and 100 weight states, respectively. The proposed photosynaptic device technology capable of optoelectronic spike processing is expected to play a crucial role in the implementation of neuromorphic computing in the future.
Postsynthetic Surface Trap Removal of CsPbX3 (X = Cl, Br, or I) Quantum Dots via a ZnX2/Hexane Solution toward an Enhanced Luminescence Quantum Yield

The control of surface properties of all inorganic cesium lead halide perovskite (CsPbX3; X = Cl, Br, or I) quantum dots (QDs) is essential to achieve excellent stability and high photoluminescence quantum yields (PLQYs). Herein, a facile method was performed to simultaneously enhance the stability and PLQYs of CsPbX3 QDs by a ZnX2/hexane solution post-treatment. We show that the halogen defect on the surface of CsPbX3 QDs can be treated in a controlled way, whereby the “black dots” that adhered on the surface as observed by transmission electron microscopy have be completely removed, resulting in enhanced stability and photoluminescence. The PLQYs of CsPbCl3, CsPbBr3, and CsPbI3 increased from 4, 58, and 63% to 86, 93, and 95%, respectively, and the origin of the “black dots” as well as their transformation mechanism has been demonstrated. As a result, the poly(dimethylsiloxane) composite films created by encapsulating stable and nearly defect-free green-emitting CsPbBr3, the red-emitting K2SiF6:Mn4+ pho.
Exploring the Potential Mechanism of Xiaokui Jiedu Decoction for Ulcerative Colitis Based on Network Pharmacology and Molecular Docking

Introduction Network pharmacology is in line with the holistic characteristics of TCM and can be used to elucidate the complex network of interactions between disease-specific genes and compounds in TCM herbal medicines. Here, we investigate the pharmacological mechanism of Xiaokui Jiedu decoction (XJD) for the treatment of ulcerative colitis (UC). Methods The Computational Systems Biology Laboratory Platform (TCMSP) database was searched and screened for the active ingredients of all drugs in XJD. The Uniport database was used to retrieve possible gene targets for the therapeutic effects of XJD. GeneCards, PharmGKB, TTD, and OMIM databases were used to retrieve XJD-related gene targets. A herb-compound-protein network and a protein-protein interaction (PPI) network were constructed, and hub genes were screened for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking was performed to validate the interrelationship between disease target proteins and active drug components. Results A total of 135 XJD potential action targets, 5097 UC-related gene targets, and 103 XJD-UC intersection gene targets were screened. The hub gene targets of XJD that exert therapeutic effects on UC are RB1, MAPK1, TP53, JUN, NR3C1, MAPK3, and ESR1. GO enrichment analysis showed 741 biofunctional enrichments, and KEGG enrichment analysis showed 124 related pathway enrichments. Molecular docking showed that the active components of XJD (β-sitosterol, kaempferol, formononetin, quercetin, and luteolin) showed good binding activities to five of the six hub gene targets. Discussion. The active ingredients of XJD (β-sitosterol, kaempferol, formononetin, quercetin, and luteolin) may regulate the inflammatory and oxidative stress-related pathways of colon cells during the course of UC by binding to the hub gene targets. This may be a potential mechanism of XJD in the treatment of UC.
Synthesis of 2D Zn–Co LDH nanosheets by a successive ionic layer deposition method as a material for electrodes of high-performance alkaline battery–supercapacitor hybrid devices

In recent years, increasing attention directed at creating novel two-dimensional graphene-like materials, in particular materials based on oxides or hydroxides of transition metals, as they have a number of unique properties, which determine the perspective of their application in various fields of electronics and electrical engineering, as well as in energy storage devices. In this paper we propose a novel promising route for the synthesis of nanolayer layered double hydroxides on the basis of zinc and cobalt by a successive ionic layer deposition method. The obtained nanolayers were characterized by SEM, EDX, XRD, HRTEM, XPS and FT-IR. The results show the synthesized nanolayers were formed from two-dimensional nanocrystals with the thickness of about 6–9 nm and the morphology of the so-called “nanosheets” with the hydrotalcite-like crystal structure of an LDH. In addition, the obtained nanolayers were investigated as electrode materials for alkaline battery–supercapacitor hybrid devices and demonstrated a high specific capacitance (270 mA h g−1 at 1 A g−1) and excellent electrochemical stability (3% drop in capacity after 1000 charge–discharge cycles).
Establishing innovative partnerships to support transitions from early intervention to preschool in the United States of America: lessons from parent and provider experiences

ABSTRACT In the United States, families of young children with developmental disabilities may encounter many challenges and obstacles when advocating for their child’s developmental services and supports. Research has highlighted that the transition from early intervention services to school-based services is especially confusing and difficult for many families. To limit confusion, the context and procedures of the transition must be clearly understood by all parties involved, including the family, early intervention providers, and school personnel. This exploratory qualitative pilot study highlights different practices used in a transition classroom for young children with developmental disabilities and the experiences of those involved in the transition process. The transition classroom was created through a collaboration between a non-profit early intervention organisation and a public Early Childhood Special Education Program. A teacher, the director of the non-profit organisation, and a parent of a child in the transition classroom were interviewed. Implications emphasising effective partnerships between families, schools, and community organisations, and how to potentially build those partnerships are discussed.