Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability of graphene-based heterojunction solar cells

Bulk-heterojunction (BHJ) solar cells based on organic small molecules and polymers are the focus of increasing attention by science and commerce. In organic photovoltaic devices, a conjugated polymer layer is used as the donor, while a fullerene-based derivative is used as the acceptor. Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) is one of the most common interfacial materials used for organic BHJ solar cells. However, PEDOT:PSS is acidic and hygroscopic in nature, and it inherits microstructural inhomogeneities that cause not only gradual degradation, but a complete failure of BHJ solar cell devices. There is a growing interest in graphene-based solar cells because graphene-based materials offer ease of solution processability, high optical transparency, and high power conversion efficiency. Graphene has been actively investigated for use as a transparent conducting electrode, and as a photoactive layer in fabricating solar cell devices. Power conversion efficiency in the range of 10% to 15% for graphene and inorganic semiconductor-based hybrid heterojunction solar cells, and 15.6% for graphene-containing perovskite solar cells has been observed. Organic materials-based solar cells degrade not only from environmental exposure, but also from photo-oxidation caused by light illumination. In addition to higher power conversion efficiency, stability in graphene-based solar cells is critically important for commercial applications. In this review article, the stability of graphene-based heterojunction solar cells under atmospheric conditions is evaluated. Current studies show that the insertion of a graphene buffer layer into solar cell heterostructures stops degradation and enhances stability in solar cell devices. Long-term environmental stability of graphene-based heterojunction solar cells for commercial applications is discussed.
Tailoring of structures and permeation properties of asymmetric nanocomposite cellulose acetate/silver membranes

Cellulose acetate (CA)–silver (Ag) nanocomposite asymmetric membranes were prepared via the wet-phase inversion method by dispersing polyvinylpirrolydone-protected Ag nanoparticles in the membrane casting solutions of different compositions. Silver nanoparticles were synthesized ex situ and added to the casting solution as a concentrated aqueous colloidal dispersion. The effects of the dispersion addition on the structure and on the selective permeation properties of the membranes were studied by comparing the nanocomposites with the silver-free materials. The casting solution composition played an important role in the adequate dispersion of the silver nanoparticles in the membrane. Incorporation of nanoscale silver and the final silver content resulted in structural changes leading to an increase in the hydraulic permeability and molecular weight cut-off of the nanocomposite membranes. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 41796.
Development of antifouling polyamide thin‐film composite membranes modified with amino‐cyclodextrins and diethylamino‐cyclodextrins for water treatment

The fouling behavior of polyamide thin-film composite (TFC) membranes modified with amino- and diethylamino-cyclodextrins (CDs) through an in situ interfacial polymerization process is reported. Modified polyamide TFC membranes exhibited improved hydrophilicity, water permeability, and fouling resistance as compared to the unmodified TFC membranes, while restricting the passage of NaCl salt (98.46 ± 0.5%). The increase in hydrophilicity was attributed to the secondary and tertiary hydroxyl groups of the CDs, which were not aminated. The membranes modified with amino-CDs had increased surface roughness while the membranes modified with diethylamino-CDs had smoother surfaces. However, despite the surface roughness of the membranes modified with amino-CDs, low fouling was observed due to the highly hydrophilic surfaces, which superseded the roughness. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 40109.
Inclusion compounds of cystostatic active (C5H5)2VCl2 and (CH3C5H4)2VCl2 with α-, β- and γ-cyclodextrines: Synthesis, EPR study and microbiological behavior toward Escherichia coli

The inclusion of vanadocene dichloride (VDC) and 1,1′-dimethyl vanadocene dichloride (MeVDC) into cyclodextrines (α-CD, β-CD and γ-CD) was studied by EPR spectroscopy. It was found that VDC and MeVDC with β-CD and γ-CD form true inclusion compounds, but with α-CD, VDC and MeVDC gave only fine dispersion mixtures. The inclusion was validated by anisotropic EPR spectra of solid samples. In addition, the antimicrobial was validated by anisotropic EPR spectra of solid samples. In addition, the antimicrobial behavior (against E. coli) of each of the complexes was determined. It was established that not only did VDC and MeVDC cause elongation of E. coli, but also the new vanadocene inclusion complexes were effective in this regard.
Novel Methods for Variable Selection in Non-faithful Domains, Understanding Support Vector Machines, Learning Regions of Bayesian Networks, and Prediction Under Manipulation

Vanderbilt University, Nashville, TN Dec. 2009 Ph.D., Department of Biomedical Informatics “Novel Methods for Variable Selection in Non-Faithful Domains, Understanding Support Vector Machines, Learning Regions of Bayesian Networks, and Prediction Under Manipulation” Advisor: Dr. Ioannis Tsamardinos & Dr. Douglas Hardin M.S., Department of Biomedical Informatics May 2005 “An Empirical Evaluation of State-of-the-Art and Novel Bayesian Network Learning Algorithms”
Composite of hierarchical interpenetrating 3D hollow carbon skeleton from lotus pollen and hexagonal MnO2 nanosheets for high-performance supercapacitors

Numerous novel materials for the next-generation of energy storage and conversion devices have been prepared through simple and green methods to meet the urgent requirement for sustainable development. In this regard, lotus pollen, which is cheap and common biomass waste, can be used as a potential carbon source for developing efficient electrode materials with a unique structure for high-performance supercapacitors. Following this aim, we successfully prepared hierarchical and interpenetrating three-dimensional (3D) hollow MnO2/C composites via a facile and rapid dipping method, employing the renewable, cost-effective and widespread naturally porous lotus pollen as both the skeleton and carbon source. Benefiting from the synergistic effect between manganese dioxide and the porous carbon matrix, the composite has a high specific capacitance of 257 F g−1 at a current density of 0.5 A g−1 and a high energy density of 51.5 W h kg−1. In addition, the prepared composite exhibits good cycling stability even after 2000 charge/discharge cycles. The approach developed in this work directs the way to take full advantage of sustainable resources provided by nature, and opens up a novel route to design and prepare high-performance materials with greater potential applications in high-performance energy storage systems.
Isonitrile, XV. Δ1‐Cyclohexenyl‐isocyanid

Δ1-Cyclohexenylisocyanid (III) wird aus 1-Cyan-1-formamino-cyclohexan (I) erhalten. An Hand der Synthese von 1-[N-Formyl-benzylamino]-cyclohexan-carbonsaure-(1)-amid (VI) wird gezeigt, das man mit Hilfe α. β-ungesattigter Isonitrile zu Kondensationsprodukten des “Isocyanwasserstoffs” gelangen kann.
Ab initio study of the absorption spectra of Agn (n=5–8) clusters

The absorption spectra of Ag5–8 have been determined in the framework of the linear response equation-of-motion coupled cluster method and related techniques employing 11-electron relativistic effective core potential. In these treatments electron correlation effects for 11 electrons per atom are included, providing an accurate description of excited states of silver clusters. The calculations of transition energies and oscillator strengths have been carried out in a large energy interval for the stable structures and for the isomeric forms higher in energy. This allowed us to investigate the influence of structural properties on the spectroscopic patterns and to determine the role of d-electrons. Inclusion of d-electrons in the correlation treatment is mandatory to obtain accurate values for transition energies, but the excitations of s-electrons are primarily responsible for the spectroscopic patterns. They are characterized by the interference phenomena known in molecular spectroscopy which lead to a s.
Identifying Candidate Optical Variables Using Gaia Data Release 2

Gaia is undertaking a deep synoptic survey of the Galaxy, but photometry from individual epochs has, as of yet, only been released for a minimal number of sources. We show that it is possible to identify variable stars in Gaia Data Release 2 by selecting stars with unexpectedly large photometric uncertainties given their brightness and number of observations. By comparing our results to existing catalogs of variables, we show that information on the amplitude of variability is also implicitly present in the Gaia photometric uncertainties. We present a catalog of about 9.3 million candidate variable stars, and discuss its limitations and prospects for future tests and extensions.
Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework

Deep Neural Networks (DNNs) have achieved extraordinary performance in various application domains. To support diverse DNN models, efficient implementations of DNN inference on edge-computing platforms, e.g., ASICs, FPGAs, and embedded systems, are extensively investigated. Due to the huge model size and computation amount, model compression is a critical step to deploy DNN models on edge devices. This paper focuses on weight quantization, a hardware-friendly model compression approach that is complementary to weight pruning.Unlike existing methods that use the same quantization scheme for all weights, we propose the first solution that applies different quantization schemes for different rows of the weight matrix. It is motivated by (1) the distribution of the weights in the different rows are not the same; and (2) the potential of achieving better utilization of heterogeneous FPGA hardware resources. To achieve that, we first propose a hardware-friendly quantization scheme named sum-of-power-of-2 (SP2) suitable for Gaussian-like weight distribution, in which the multiplication arithmetic can be replaced with logic shifter and adder, thereby enabling highly efficient implementations with the FPGA LUT resources. In contrast, the existing fixed-point quantization is suitable for Uniform-like weight distribution and can be implemented efficiently by DSP. Then to fully explore the resources, we propose an FPGA-centric mixed scheme quantization (MSQ) with an ensemble of the proposed SP2 and the fixed-point schemes. Combining the two schemes can maintain, or even increase accuracy due to better matching with weight distributions.For the FPGA implementations, we develop a parameterized architecture with heterogeneous Generalized Matrix Multiplication (GEMM) cores—one using LUTs for computations with SP2 quantized weights and the other utilizing DSPs for fixed-point quantized weights. Given the partition ratio among the two schemes based on resource characterization, MSQ quantization training algorithm derives an optimally quantized model for the FPGA implementation. We evaluate our FPGA-centric quantization framework across multiple application domains. With optimal SP2/fixed-point ratios on two FPGA devices, i.e., Zynq XC7Z020 and XC7Z045, we achieve performance improvement of 2.1 × -4.1 × compared to solely exploiting DSPs for all multiplication operations. In addition, the CNN implementations with the proposed MSQ scheme can achieve higher accuracy and comparable hardware utilization efficiency compared to the state-of-the-art designs.
RESIDUE MANAGEMENT AND WATER DELIVERY EFFECTS ON SEASON-LONG SURFACE SOIL WATER DYNAMICS IN SOYBEAN

Without at least equivalent recharge, groundwater withdrawals for irrigation purposes can lead to aquifer depletion and concern for the long-term sustainability of irrigated agriculture, such as the case with the shallow Alluvial Aquifer underlying much of the Mississippi River Delta region of the midsouthern United States. Thus, improving agricultural water-use efficiency, through the use of alternative residue management practices that have the potential to conserve soil water, is essential. The objective of this study was to evaluate the effects of tillage, residue burning, residue level, and water delivery (i.e., furrow irrigation or rainfall) on soil water content dynamics in the soybean [Glycine max (L.) Merr. ] root zone of a Calloway silt loam (fine-silty, mixed, active, thermic, Aquic Fraglossudalf) in a wheat (Triticum aestivum L.)-soybean double-crop production system in eastern Arkansas. Soil water contents at a 7.5-cm depth were continuously recorded using water content reflectometers throughout the 2005 and 2006 soybean-growing seasons. Maximum soil water contents were significantly greater (P < 0.05) after irrigation events and numerically greater after rainfall events with the burned compared with the nonburned treatment. Minimum soil water contents were also numerically greater when residue was burned, but the soil in the nonburn treatment dried down more slowly. Although similar maximum soil water contents were achieved under conventional tillage and no-tillage (NT), NT soil consistently dried down more slowly and maintained numerically greater minimum water contents, thus conserving soil water more effectively under NT than conventional tillage. Even slight differences in soil water dynamics among residue management practices can result in substantial water conservation, which is imperative for sustainable row-crop agriculture in the Mississippi River Delta region of the midsouthern United States and irrigation cost savings.
Evaluation of an ATP Assay to Quantify Bacterial Attachment to Surfaces in Reduced Gravity

Aim: To develop an assay to quantify the biomass of attached cells and biofilm formed on wetted surfaces in variable-gravity environments. Methods and Results: Liquid cultures of Pseudomonas aeruginosa were exposed to 30-35 brief cycles of hypergravity (< 2-g) followed by free fall (i.e., reduced gravity) equivalent to either lunar-g (i.e., 0.17 normal Earth gravity) or micro-g (i.e., < 0.001 normal Earth gravity) in an aircraft flying a series of parabolas. Over the course of two days of parabolic flight testing, 504 polymer or metal coupons were exposed to a stationary-phase population of P. aeruginosa strain ERC1 at a concentration of 1.0 x 10(exp 5) cells per milliliter. After the final parabola on each flight test day, half of the material coupon samples were treated with either 400 micro-g/L ionic silver fluoride (microgravity-exposed cultures) or 1% formalin (lunar-gravity-exposed cultures). The remaining sample coupons from each flight test day were not treated with a fixative. All samples were returned to the laboratory for analysis within 2 hours of landing, and all biochemical assays were completed within 8 hours of exposure to variable gravity. The intracellular ATP luminescent assay accurately reflected cell physiology compared to both cultivation-based and direct-count microscopy analyses. Cells exposed to variable gravity had more than twice as much intracellular ATP as control cells exposed only to normal Earth gravity.
Semantic and Geometric Modeling with Neural Message Passing in 3D Scene Graphs for Hierarchical Mechanical Search

Searching for objects in indoor organized environments such as homes or offices is part of our everyday activities. When looking for a desired object, we reason about the rooms and containers the object is likely to be in; the same type of container will have a different probability of containing the target depending on which room it is in. We also combine geometric and semantic information to infer what container is best to search, or what other objects are best to move, if the target object is hidden from view. We use a 3D scene graph representation to capture the hierarchical, semantic, and geometric aspects of this problem. To exploit this representation in a search process, we introduce Hierarchical Mechanical Search (HMS), a method that guides an agent’s actions towards finding a target object specified with a natural language description. HMS is based on a novel neural network architecture that uses neural message passing of vectors with visual, geometric, and linguistic information to allow HMS to process data across layers of the graph while combining semantic and geometric cues. HMS is trained on 1000 3D scene graphs and evaluated on a novel dataset of 500 3D scene graphs with dense placements of semantically related objects in storage locations, and is shown to be significantly better than several baselines at finding objects. It is also close to the oracle policy in terms of the median number of actions required. Additional qualitative results can be found at https://ai.stanford. edu/mech-search/hms
Wideband Beam Tracking in THz Massive MIMO Systems

Terahertz (THz) massive multiple-input multiple-output (MIMO) has been considered as one of the promising technologies for future 6G wireless communications. It is essential to obtain channel information by beam tracking scheme to track mobile users in THz massive MIMO systems. However, the existing beam tracking schemes designed for narrowband systems with the traditional hybrid precoding structure suffer from a severe performance loss caused by the beam split effect, and thus cannot be directly applied to wideband THz massive MIMO systems. To solve this problem, in this paper we propose a beam zooming based beam tracking scheme by considering the recently proposed delay-phase precoding structure for THz massive MIMO. Specifically, we firstly prove the beam zooming mechanism to flexibly control the angular coverage of frequency-dependent beams over the whole bandwidth, i.e., the degree of the beam split effect, which can be realized by the elaborate design of time delays in the delay-phase precoding structure. Then, based on this beam zooming mechanism, we propose to track multiple user physical directions simultaneously in each time slot by generating multiple beams. The angular coverage of these beams is flexibly zoomed to adapt to the potential variation range of the user physical direction. After several time slots, the base station is able to obtain the exact user physical direction by finding out the beam with the largest user received power. Unlike traditional schemes where only one frequency-independent beam can be usually generated by one radio-frequency chain, the proposed beam zooming based beam tracking scheme can simultaneously track multiple user physical directions by using multiple frequency-dependent beams generated by one radio-frequency chain. Theoretical analysis shows that the proposed scheme can achieve the near-optimal achievable sum-rate performance with low beam training overhead, which is also verified by extensive simulation results.
The origin of the dust extinction curve in milky way-like galaxies

We develop a cosmological model for the evolution of dust grains in galaxies with a distribution of sizes in order to understand the origin of the Milky Way dust extinction curve. Our model considers the formation of active dust in evolved stars, growth by accretion and coagulation, and destruction processes via shattering, sputtering, and astration in the ISM of galaxies over cosmic time. Our main results follow. Galaxies in our cosmological model with masses comparable to the Milky Way’s at z ∼ 0 exhibit a diverse range of extinction laws, though with slopes and bump strengths comparable to the range observed in the Galaxy. The progenitors of the Milky Way have steeper slopes, and only flatten to slopes comparable to the Galaxy at z ∼ 1. This owes to increased grain growth rates at late times/in high-metallicity environments driving up the ratio of large to small grains, with a secondary dependence on the graphite-to-silicate ratio evolution. The UV bump strengths depend primarily on the graphite-to-silicate ratio, and remain broadly constant in MW-like galaxies between z = 3 and z = 0, though show slight variability. Our models span comparable regions of bump-slope space as sightlines in the Galaxy do, though there is a lack of clear relationship between the model slopes and bump strengths owing to variations among galaxies in the graphite-to-silicate ratio. Our model provides a novel framework to study the origins and variations of dust extinction curves in galaxies over cosmic time.
Quantum LDPC Codes With Almost Linear Minimum Distance

We give a construction of quantum LDPC codes of dimension <inline-formula> <tex-math notation="LaTeX">$\Theta (\log N)$ </tex-math></inline-formula> and distance <inline-formula> <tex-math notation="LaTeX">$\Theta (N/\log N)$ </tex-math></inline-formula> as the code length <inline-formula> <tex-math notation="LaTeX">$N\to \infty $ </tex-math></inline-formula>. Using a product of chain complexes this construction also provides a family of quantum LDPC codes of distance <inline-formula> <tex-math notation="LaTeX">$\Omega (N^{1-\alpha /2}/\log N)$ </tex-math></inline-formula> and dimension <inline-formula> <tex-math notation="LaTeX">$\Omega (N^\alpha \log N)$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$0 \le \alpha < 1$ </tex-math></inline-formula>. We also introduce and study a new operation called lifted product, which naturally generalizes the product operations for quantum codes and chain complexes. Moreover, as a simple byproduct of our results on quantum codes, we obtain a new result on classical codes. We show that for any fixed <inline-formula> <tex-math notation="LaTeX">$R < 1$ </tex-math></inline-formula> there exists an asymptotically good family of classical quasi-cyclic LDPC codes of rate at least <inline-formula> <tex-math notation="LaTeX">$R$ </tex-math></inline-formula> with, in some sense, optimal circulant size <inline-formula> <tex-math notation="LaTeX">$\Omega (N/\log N)$ </tex-math></inline-formula> as the code length <inline-formula> <tex-math notation="LaTeX">$N\to \infty $ </tex-math></inline-formula>.
Increase of Low-Frequency Modes of User Dynamics in Online Social Networks During Overheating of Discussions

User dynamics in online social networks have a significant impact on not only the online community but also real-world activities. As examples, we can mention the occurrence of explosive user dynamics triggered by social polarization, echo chamber phenomena, fake news, etc. Explosive user dynamics collectively refer to the phenomenon of flaming. The wave equation-based model for online social networks (called the oscillation model) is a theoretical model proposed to describe user dynamics in online social networks. This model can be used to understand the relationship between the occurrence of explosive user dynamics such as flaming and the structure of social networks. However, since the oscillation model was introduced as a purely theoretical construct with regard to social networks, it is necessary to confirm whether the model describes real phenomena correctly or not. In this paper, we first show a prediction from the oscillation model in which the low-frequency oscillation mode of user dynamics will be dominant when user activity in online social networks is increased. To verify the predictions with actual data, we show spectral analyses of both the log data of posts on an electronic bulletin board site and the frequency data of word search from Google Trends. The results support well and thus validate the predictions of the theory.