Glass forming ability of Zr–Al–Ni(Co,Cu) understood via cluster sharing model

AbstractClusters are shared atoms in different ways with their neighboring clusters in the crystalline phases. Cluster formula [effective cluster]1(glue atom)x can be used to describe crystalline phases, and the effective cluster means the true cluster composition due to cluster overlapping in the phase structure. Degree of cluster sharing of Zr6Al2Ni (InMg2), Zr2Co (Al2Cu) and Zr2Cu (MoSi2) phases is investigated in this paper. Ni3Zr9, Co3Zr8 and Cu5Zr10 clusters are highlighted because they have the least degree of sharing and can best represent the local atomic short-range order features of the formed phases. It is pointed out that the least sharing clusters are correlated with metallic glass formation and are verified by experiments

Battery-type column for caesium ions separation using electroactive film of copper hexacyanoferrate nanoparticles

We reported a novel and compact battery-type column using nanoparticles film of copper hexacyanoferrate (CuHCF NPs film) for sequential removal of Cs from wastewater. Different from the electrochemical deposition, chemical spray or chemical bath deposition, our film was prepared by coating water dispersed CuHCF NPs ink on the electrode surface through a simple wet process similar to ink printing. The battery-type column indicated Cs adsorption and desorption can be achieved by electrochemical redox of CuHCF NPs film, through switching the potentials between two sandwiched electrodes. Kinetic studies revealed both the static attraction and electrochemical oxidation-reduction of Fe (II/III) contributed to Cs separation. Insignificant change in the current after 100\ua0cycles of durability test indicated the CuHCF NPs film is relatively stable, suggesting the battery-type column has a long service life for Cs removal from wastewater

CycleAlign: Iterative Distillation from Black-box LLM to White-box Models for Better Human Alignment

Language models trained on large-scale corpus often generate content that is harmful, toxic, or contrary to human preferences, making their alignment with human values a critical concern. Reinforcement learning from human feedback (RLHF) with algorithms like PPO is a prevalent approach for alignment but is often complex, unstable, and resource-intensive. Recently, ranking-based alignment methods have emerged, offering stability and effectiveness by replacing the RL framework with supervised fine-tuning, but they are costly due to the need for annotated data. Considering that existing large language models (LLMs) like ChatGPT are already relatively well-aligned and cost-friendly, researchers have begun to align the language model with human preference from AI feedback. The common practices, which unidirectionally distill the instruction-following responses from LLMs, are constrained by their bottleneck. Thus we introduce CycleAlign to distill alignment capabilities from parameter-invisible LLMs (black-box) to a parameter-visible model (white-box) in an iterative manner. With in-context learning (ICL) as the core of the cycle, the black-box models are able to rank the model-generated responses guided by human-craft instruction and demonstrations about their preferences. During iterative interaction, the white-box models also have a judgment about responses generated by them. Consequently, the agreement ranking could be viewed as a pseudo label to dynamically update the in-context demonstrations and improve the preference ranking ability of black-box models. Through multiple interactions, the CycleAlign framework could align the white-box model with the black-box model effectively in a low-resource way. Empirical results illustrate that the model fine-tuned by CycleAlign remarkably exceeds existing methods, and achieves the state-of-the-art performance in alignment with human value

A Fast Clustering Algorithm based on pruning unnecessary distance computations in DBSCAN for High-Dimensional Data

Clustering is an important technique to deal with large scale data which are explosively created in internet. Most data are high-dimensional with a lot of noise, which brings great challenges to retrieval, classification and understanding. No current existing approach is “optimal” for large scale data. For example, DBSCAN requires O(n2) time, Fast-DBSCAN only works well in 2 dimensions, and ρ-Approximate DBSCAN runs in O(n) expected time which needs dimension D to be a relative small constant for the linear running time to hold. However, we prove theoretically and experimentally that ρ-Approximate DBSCAN degenerates to an O(n2) algorithm in very high dimension such that 2D >  > n. In this paper, we propose a novel local neighborhood searching technique, and apply it to improve DBSCAN, named as NQ-DBSCAN, such that a large number of unnecessary distance computations can be effectively reduced. Theoretical analysis and experimental results show that NQ-DBSCAN averagely runs in O(n*log(n)) with the help of indexing technique, and the best case is O(n) if proper parameters are used, which makes it suitable for many realtime data

A 3D-printed microfluidic-enabled hollow microneedle architecture for transdermal drug delivery.

Embedding microfluidic architectures with microneedles enables fluid management capabilities that present new degrees of freedom for transdermal drug delivery. To this end, fabrication schemes that can simultaneously create and integrate complex millimeter/centimeter-long microfluidic structures and micrometer-scale microneedle features are necessary. Accordingly, three-dimensional (3D) printing techniques are suitable candidates because they allow the rapid realization of customizable yet intricate microfluidic and microneedle features. However, previously reported 3D-printing approaches utilized costly instrumentation that lacked the desired versatility to print both features in a single step and the throughput to render components within distinct length-scales. Here, for the first time in literature, we devise a fabrication scheme to create hollow microneedles interfaced with microfluidic structures in a single step. Our method utilizes stereolithography 3D-printing and pushes its boundaries (achieving print resolutions below the full width half maximum laser spot size resolution) to create complex architectures with lower cost and higher print speed and throughput than previously reported methods. To demonstrate a potential application, a microfluidic-enabled microneedle architecture was printed to render hydrodynamic mixing and transdermal drug delivery within a single device. The presented architectures can be adopted in future biomedical devices to facilitate new modes of operations for transdermal drug delivery applications such as combinational therapy for preclinical testing of biologic treatments

A Low-Profile Beam-Steering Reflectarray with Integrated Leaky-Wave Feed and 2-Bit Phase Resolution for Ka-band SatCom

© 2021 IEEE - All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/TAP.2021.3111172A novel reflect array (RA) with ultra-low-profile and 2-bit phase quantization beam-steering ability is presented in this paper. To reduce the profile, a Leaky-wave feed is used to excite the RA with enhanced illumination efficiency. Moreover, simultaneous sum and difference patterns are also obtained to provide beam flexibility. The entire thickness of the proposed RA is less than 3% of that of the conventional front-fed RA with the same aperture. To increase the efficiency of the RA, a novel unit cell consisting of a polarizer layer and a reflection layer is developed, which is configured to provide polarization rotation and 2-bit phase shifts by using a hybrid of tunable polarization and discrete resonator. The operation principle, theoretical explanation, and implementation of the proposed antenna are elaborated in this work. To prove the design concept and beam scanning performance, an array with 9×7 unit cells operating atKa-band is designed and simulated firstly. 2-D beam scanning within the range of ±30º has been verified. Then, a passive prototype with 9×67 unit cells is designed, fabricated and measured. Experimental results show aperture efficiency of35.1% and illumination efficiency of 43.4%. The developed RA is scalable, and it provides a viable low-cost solution to develop low-profile, high-gain and beam-steering array antennas for satellite applicationsPeer reviewe

A New Equivalent Statistical Damage Constitutive Model on Rock Block Mixed Up with Fluid Inclusions

So far, there are few studies concerning the effect of closed “fluid inclusions” on the macroscopic constitutive relation of deep rock. Fluid-matrix element (FME) is defined based on rock element in statistical damage model. The properties of FME are related to the size of inclusions, fluid properties, and pore pressure. Using FME, the equivalent elastic modulus of rock block containing fluid inclusions is obtained with Eshelby inclusion theory and the double M-T homogenization method. The new statistical damage model of rock is established on the equivalent elastic modulus. Besides, the porosity and confining pressure are important influencing factors of the model. The model reflects the initial damage (void and fluid inclusion) and the macroscopic deformation law of rock, which is an improvement of the traditional statistical damage model. Additionally, the model can not only be consistent with the rock damage experiment date and three-axis compression experiment date of rock containing pore water but also describe the locked-in stress experiment in rock-like material. It is a new fundamental study of the constitutive relation of locked-in stress in deep rock mass

Enzyme characterization and biological activities of a resuscitation promoting factor from an oil degrading bacterium Rhodococcus erythropolis KB1

Resuscitation-promoting factors (Rpf) are a class of muralytic enzymes, which participate in recovery of dormant cells and promoting bacteria growth in poor media. In the present study the expression vector of the rpf-1 gene from an oil-degrading bacterium Rhodococcus erythropolis KB1 was constructed and expressed in Escherichia coli. The expressed protein was purified by Ni2+-affinity chromatography, and showed muralytic activity when measured with 4-methylumbelliferyl-β-D-N,N′,N″-triacetyl chitotrioside as substrate. Addition of purified Rpf-1 to R. erythropolis culture efficiently improved bacterial cell growth. The purified protein also increased resuscitation of viable but nonculturable cells of R. erythropolis to culturable state. The conserved amino acid residues including Asp45, Glu51, Cys50, Thr60, Gln69, Thr74, Trp75 and Cys114 of the Rpf-1 were replaced with different amino acids. The mutant proteins were also expressed and purified with Ni2+-affinity chromatography. The muralytic activities of the mutant proteins decreased to different extents when compared with that of the wild type Rpf-1. Gln69 was found to play the most important role in the enzyme activity, substitution of Gln69 with lysine (Q69K) resulted in the greatest decrease of muralytic activity. The other amino acid residues such as Asp45, Glu51, Cys50 and Cys114 were also found to be very important in maintaining muralytic activity and biological function of the Rpf-1. Our results indicated that Rpf-1 from R. erythropolis showed muralytic activities and weak protease activity, but the muralytic activity was responsible for its growth promotion and resuscitation activity