Miracle-dz/UniFAR-FTUs huggingface dataset:
A Taguchi approach to synthesise Al/Fe core–shell composite powders through electroless deposition

ABSTRACT In the present study, Al/Fe core–shell particles were successfully synthesised by electroless deposition of iron on aluminium particles. The process variables were investigated and optimised to achieve maximum deposition efficiency. These variables, including chemical composition parameters (molar ratios of salt/reducing agent, salt/complexing agent and pH) and process parameters (particle size, temperature and time) were optimised by using the Taguchi method. The chemical composition of iron deposited aluminium particles, their morphology and coating quality were characterised by helium gas pycnometry, scanning electron microscopy, energy-dispersive spectroscopy and X-ray diffraction. The results revealed that, by using the optimised bath chemical composition and optimised process parameters, a maximum of 28.91% iron deposition on aluminium particles can be obtained within 20 min.
Hybrid Optimized Approaches for Routing and Resource Reservation Protocols in Optical Networks

We have proposed hybrid approaches to solve dynamic provisioning problems in fixed-grid and elastic optical networks (EON). The proposed approaches use the information from the optimization models, which normally are used to solve static problems, to guide the search for a good solution in dynamic networking. We have presented three models, i.e., Route-Model, RouteRes-Model, and RouteEON-Model. Route-Model computes routing information which is integrated with the first-fit algorithm. RouteRes-Model computes routes and a set of wavelengths for each end pair. Both models are utilized for dynamic provisioning of routing and wavelength assignment in fixed-grid networks. Similarly, RouteEON-Model considers the elastic characteristics of flexible networks and computes routing information. This is integrated with the first-fit algorithm for dynamic provisioning. The proposed solutions efficiently reduce the blocking probability (BP) in fixed-grid networks and the bandwidth BP in EON compared to the shortest path first (SPF) routing and alternate ($k=2$) routing. Similarly, RouteRes-Model achieved high wavelength utilization compared to other solutions. Finally, the proposed solutions utilized approximately equal number of paths compared to SPF routing. However, compared to SPF routing, Route-Model and RouteRes-Model supported approximately 43% and 66% more traffic respectively while alternate routing supported 36% more traffic for the same values of BPs.
Research on the Degradation Characteristics of IGBT Safe Operation Area(SOA) in Traction Converter

IGBT is the core part in traction converter, its performance directly affects the design characteristics of the converter. Ensure IGBT works in its own safe operation area(SOA) can improve the reliability of traction converter, decrease failure rate and extend service life. Based on the aging mechanism of traction converter IGBT, this paper studies on the degradation of boundary characteristic parameter of IGBT safe operation area(SOA), which include maximum collector continuous current $I_{CDC}$, maximum collector power consumption $P_{Cmax}$ and short-circuit saturated current $I_{SC, sat}$, buliding the dynamic models of DC safe operation area (DCSOA) and short circuit safe operation area (SCSOA) in IGBT life cycle. this model has certain theoretical significance and application value for IGBT condition monitoring.
Research on the Working Characteristics of the Power Transmission Mechanism of a New Type of Spherical Power Source

The spherical power source is a new type of energy conversion device. Its design concept is to integrate the functions of the spherical engine and the generator. The fuel chemical energy can be directly and efficiently converted into electrical energy output. Its spherical structure greatly improves the utilization of the space. It can be carried by one person after miniaturization design. Therefore, it has a broad application prospect. Firstly, the structure and the working principle of the spherical power source are introduced in this paper. The profile model and the machining method of the spatial guide CAM are analyzed. Then its power transmission mechanism is simulated based on the multi-body dynamics software. The prototype of the spherical power source is manufactured. The prototype runs normally during the motor drive test. Finally, the vibration characteristics of the prototype are studied experimentally. The test vibration level is 1. All vibration data meet the requirements specified in SY/T 5641-2019 Standard. Therefore, the configuration scheme designed in this paper is feasible. However, due to certain machining error and assembly error, there is a certain mechanical shock when the power source is running. In the follow-up research, some key transmission part is necessary to design flexibly, so as to ensure the smooth operation of the power source. This paper lays the foundation of configuration design for the following research.
Monosomies, trisomies and segmental aneuploidies differentially affect chromosomal stability

Aneuploidy and chromosomal instability are both commonly found in cancer. Chromosomal instability leads to karyotype heterogeneity in tumors and is associated with therapy resistance, metastasis and poor prognosis. It has been hypothesized that aneuploidy per se is sufficient to drive CIN, however due to limited models and heterogenous results, it has remained controversial which aspects of aneuploidy can drive CIN. In this study we systematically tested the impact of different types of aneuploidies on the induction of CIN. We generated a plethora of isogenic aneuploid clones harboring whole chromosome or segmental aneuploidies in human p53-deficient RPE-1 cells. We observed increased segregation errors in cells harboring trisomies that strongly correlated to the number of gained genes. Strikingly, we found that clones harboring only monosomies do not induce a CIN phenotype. Finally, we found that an initial chromosome breakage event and subsequent fusion can instigate breakage-fusion-bridge cycles in segmental aneuploidies. This suggests that monosomies, trisomies and segmental aneuploidies have fundamentally different effects on chromosomal instability and these results help us to decipher the complex relationship between aneuploidy and CIN.
Sharper $N$-D Heisenberg's Uncertainty Principle

A sharper uncertainty inequality which exhibits a lower bound tighter than that in the classical <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula>-dimensional Heisenberg's uncertainty principle is obtained. The condition that reaches an equality relation of the uncertainty inequality is deduced. Example and simulations are carried out to illustrate that the newly derived uncertainty principle is truly sharper than the classical one. The new proposal's applications in time-frequency analysis, optical signal processing and physical optics propagation are also given.
Research on Multimodality in Aerodynamic/Stealth Airfoil Design Optimization

The airfoil on modern fighters needs large positive moment to maintain longitudinal trim in addition to good aerodynamic and stealth performance. The novel design requirements would increase the likelihood of multimodality in design space. To address this issue, this paper uses parallel niching method to identify the existence and possible sources of multimodality in the aerodynamic and stealth shape optimizations based on a symmetrical airfoil. To isolate the instances of space multimodality, several subproblems are studied by varying the number and range of design variables, as well as positive moment constraints, respectively. The results demonstrate that the occurrences of multimodality in aerodynamic design space are highly related to positive moment constraint and ranges of design variables. Additionally, it’s found that some local minimums in aerodynamic space are very close to that of stealth space, indicating that the there’s not that large conflict between aerodynamic and stealth design under certain circumstances. This discovery may appeal a new approach of aerodynamic/stealth design of aircraft.
Potential role of epicardial adipose tissue in coronary artery endothelial cell dysfunction in type 2 diabetes

Cardiovascular disease is the most prevalent cause of morbidity and mortality in diabetes. Epicardial adipose tissue (EAT) lies in direct contact with the myocardium and coronary arteries and can influence cardiac (patho) physiology through paracrine signaling pathways. This study hypothesized that the proteins released from EAT represent a critical molecular link between the diabetic state and coronary artery endothelial cell dysfunction. To simulate type 2 diabetes‐associated metabolic and inflammatory status in an ex vivo tissue culture model, human EAT samples were treated with a cocktail composed of high glucose, high palmitate, and lipopolysaccharide (gplEAT) and were compared with control EAT (conEAT). Compared to conEAT, gplEAT showed a markedly increased gene expression profile of proinflammatory cytokines, corroborating EAT inflammation, a hallmark feature observed in patients with type 2 diabetes. Luminex assay of EAT‐secretome identified increased release of various proinflammatory cytokines, including tumor necrosis factor‐alpha (TNF‐alpha), interferon‐alpha 2 (IFNA2), interleukin 1 beta (IL1B), interleukin 5 (IL5), interleukin 13 (IL13), and CCL5, among others, in response to high glucose, high palmitate, and lipopolysaccharide. Conditioned culture media was used to collect the concentrated proteins (CPs). In response to gplEAT‐CPs, human coronary artery endothelial cells (HCAECs) exhibited an inflammatory endothelial cell phenotype, featuring a significantly increased gene expression of proinflammatory cytokines and cell surface expression of VCAM‐1. Moreover, gplEAT‐CPs severely decreased Akt‐eNOS signaling, nitric oxide production, and angiogenic potential of HCAECs, when compared with conEAT‐CPs. These findings indicate that EAT inflammation may play a key role in coronary artery endothelial cell dysfunction in type 2 diabetes.
Unsupervised Evaluation and Optimization for Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a radiation-free, fast, and convenient tomographic technology that uses only surface electrodes. EIT has the potential to provide continuous bedside monitoring of patients, for example, during mechanical ventilation. However, the soft-field nature of EIT leads to an ill-posed reconstruction problem that often results in multiple image solutions. This is exacerbated when EIT systems are used in variable measurement setups and scenarios, as few adjustment methods or EIT calibration approaches work reliably or require a reference phantom. The goals of this work are to design quality metrics to provide feedback for the EIT process to guide the system in adjusting the algorithm and parameters, for example, to alert the system in the event of poor image quality due to electrode connection variability. This then may be dealt with by physical electrode adjustment. In this article, the metrics, OAD and AL, representing object and artifact discreteness and artifact level, were designed to evaluate EIT image quality in an unsupervised way. Based on the quality index feedback, an image optimization process is proposed. The developed metrics and optimization methods were validated through data simulated in typical circular domain and thorax scenarios, and clinical data from human respiration. The conventional supervised evaluation metric, i.e., the correlation coefficient (COR) between the reference image and the reconstructed image, was used for comparison. The accuracy of new metrics was represented as the correlation coefficient of the new metric and COR. From the results, OAD and AL could improve the image quality by optimizing regularization parameters. The accuracy results of OAD and COR in the circular domain are 0.9429 and 0.9328, and those in thorax scenarios are 0.9741 and 0.8393. OAD and AL provide the evaluation of EIT images without using any prior knowledge or reference conductivity distribution, providing feedback to improve the reliability of EIT systems and reduce the risk of erroneous diagnosis.
Imlifidase for the treatment of anti‐HLA antibody‐mediated processes in kidney transplantation

The IgG‐degrading enzyme derived from Streptococcus pyogenes (Imlifidase, Hansa Biopharma) is a novel agent that cleaves all four human subclasses of IgG and has therapeutic potential for HLA desensitization in kidney transplantation and antibody‐mediated rejection. Data from clinical trials in kidney transplantation demonstrated rapid degradation of anti‐HLA donor‐specific antibodies facilitating HLA‐incompatible transplantation, which led to conditional approval of imlifidase by the European Medicines Agency for desensitization in kidney transplant recipients of a deceased donor with a positive cross match. Important considerations arising from the early experiences with imilfidase on kinetics of donor‐specific antibodies after administration, timing of complementary therapeutic monoclonal or polyclonal IgG antibodies, and interference with cross match assays should be recognized as imlifidase emerges as a therapeutic agent for clinical transplantation.
Random Linear Streaming Codes in the Finite Memory Length and Decoding Deadline Regime

Streaming codes take a string of source symbols as input and output a string of coded symbols in real time, which effectively eliminate the queueing delay and are regarded as a promising scheme for low latency communications. Aiming at quantifying the fundamental latency performance of random linear streaming codes (RLSCs) over i.i. d. symbol erasure channels, this work derives the exact error probability under, simultaneously, the finite memory length and finite decoding deadline constraints. The result is then used to examine the tradeoff among memory length (complexity), decoding deadline (delay), and error probability (reliability) of RLSCs for the first time in the literature. Two critical observations are made: (i) Too much memory can adversely impact the performance under a finite decoding deadline constraint, a surprising finding not captured by the traditional wisdom that large memory length monotonically improves the performance in the asymptotic regime; (ii) The end-to-end delay of the RLSC is roughly 50% of that of the MDS block code when under identical code rate and error probability requirements. This implies that switching from block codes to RLSCs not only eliminates the queueing delay (thus 50%) but also has little negative impact on the error probability.
Microbiomes in drinking water treatment and distribution: a meta-analysis from source to tap

A meta-analysis of existing and available Illumina 16S rRNA datasets from drinking water source, treatment and drinking water distribution systems (DWDS) were collated to compare changes in abundance and diversity throughout. Samples from bulk water and biofilm were used to assess principles governing microbial community assembly and the value of amplicon sequencing to water utilities. Individual phyla relationships were explored to identify competitive or synergistic factors governing DWDS microbiomes. The relative importance of stochasticity in the assembly of the DWDS microbiome was considered to identify the significance of source and treatment in determining communities in DWDS. Treatment of water significantly reduces overall species abundance and richness, with chlorination of water providing the most impact to individual taxa relationships. The assembly of microbial communities in the bulk water of the source, primary treatment process and DWDS is governed by more stochastic processes, as is the DWDS biofilm. DWDS biofilm is significantly different from bulk water in terms of local contribution to beta diversity, type and abundance of taxa present. Water immediately post chlorination has a more deterministic microbial assembly, highlighting the significance of this process in changing the microbiome, although elevated levels of stochasticity in DWDS samples suggest that this may not be the case at customer taps. 16S rRNA sequencing is becoming more routine, and may have several uses for water utilities, including: detection and risk assessment of potential pathogens such as those within the genera of Legionella and Mycobacterium; assessing the risk of nitrification in DWDS; providing improved indicators of process performance and monitoring for significant changes in the microbial community to detect contamination. Combining this with quantitative methods like flow cytometry will allow a greater depth of understanding of the DWDS microbiome.
Global Relation-Aware Attention Network for Image-Text Retrieval

The cross-modal image-text retrieval has attracted extensive attention in recent years, which contributes to the development of search engine. Fine-grained features and cross-attention have been widely used in past researches to reach the goal of cross-modal image-text matching. Although cross-related methods have achieved remarkable results, the features must be encoded again in evaluation phase due to the interaction of the two modalities, which is unsuitable for actual scenarios of search engine development. In addition, the aggregated feature does not contain sufficient semantics since it is merely obtained by simple mean pooling. Furthermore, connecting weights of self-attention blocks are target position invariant, which lacks the expected adaptability. To tackle these limitations, in this paper, we propose a novel Global Relation-aware Attention Network (GRAN) for image-text retrieval by designing Global Attention Module (GAM) and Relation-aware Attention Module (RAM) which play an important role in modeling the global feature and the relationships of local fragments. Firstly, we propose Global Attention Module (GAM) followed the fine-grained features to obtain meaningful global feature. Secondly, we use several stacked transformer encoders to further encode features separately. Finally, we propose Relation-aware Attention Module (RAM) to generate a vector which represents the relation information to infer the attention intensity of pairwise fragments. The local features, the global feature, and their relations are considered jointly to conduct an efficient image-text retrieval. Extensive experiments are conducted on the benchmark datasets of Flickr30K and MSCOCO, demonstrating the superiority of our method. On the Flickr30K, compared to the state-of-the-art method TERAN, we improve Recall@K(K=1) metric by 5.8% and 4.0 on the image and text retrieval tasks, respectively.
Decoding for Optimal Expected Normalized Distance over the t-Deletion Channel

This paper studies optimal decoding for a special case of the deletion channel, referred by the t-deletion channel, which deletes exactly $t$ symbols of the transmitted word uniformly at random. The goal of the paper is to understand how such an optimal decoder operates in order to minimize the expected normalized distance. A full characterization of a decoder for this setup is given for a channel that deletes one or two symbols. For $t$ = 1 it is shown that when the code is the entire space, the decoder is the lazy decoder which simply returns the channel output. Similarly, for $t$ = 2 it is shown that the decoder acts as the lazy decoder in almost all cases and when the longest run is significantly long, it prolongs the longest run by one symbol.
A Generalized notion of Sufficiency for Power-law Distributions

We propose a generalized notion of principle of sufficiency when the underlying inference method is not necessarily maximum likelihood. This notion is based on certain generalized likelihood functions that arise in robust inference problems. Particularly, in this paper, we consider the Basu et al. estimation [1]. We identify the specific form of the probability distributions that have a fixed number of sufficient statistics with respect to this estimation. These distributions are power-law in nature and Student distributions are a part of this family.
Bayesian Adaptive Path Allocation Techniques for Intra-Datacenter Workloads

Data center networks (DCNs) are the backbone of many cloud and Internet services. They are vulnerable to link failures, that occur on a daily basis, with a high frequency. Service disruption due to link failure may incur financial losses, compliance breaches and reputation damage. Performance metrics such as packet loss and routing flaps are negatively affected by these failure events. We propose a new Bayesian learning approach towards adaptive path allocation that aims to improve DCN performance by reducing both packet loss and routing flaps ratios. The proposed approach incorporates historical information about link failure and usage probabilities into its allocation procedure, and updates this information on-the-fly during DCN operational time. We evaluate the proposed framework using an experimental platform built with the POX controller and the Mininet emulator. Compared with a benchmark shortest path algorithm, the results show that the proposed methods perform better in terms of reducing the packet loss and routing flaps.
Efficient Short Group Signatures for Conditional Privacy in Vehicular Ad Hoc Networks via ID Caching and Timed Revocation

Vehicular Ad hoc Networks (VANETs) are a subset of the Internet of Things (IoT) that are used in smart traffic applications. Due to their high speed, mobility, and exposure to the environment, the security requirements for VANETs result in the conflicting design goals of protecting member privacy while also ensuring non-repudiation. Group signature schemes can fulfill these requirements, but often at the cost of expensive bilinear pairing operations. Furthermore, the cost of updating the group key information can be costly. Accordingly, this paper has two goals. First, it presents a group signature scheme that has been modified to remove pairing operations by caching computed values, while still preserving the critical requirement of conditional privacy. Second, this paper presents an argument for the abandonment of perfect forward and backward secrecy in VANET schemes in order to prevent the generation of keys that are never used, or used only once, and reduce the twin burdens of excessive key recalculation and key redistribution on the system.