Miracle-dz/UniFAR-FTUs huggingface dataset:
Zoonet: a proactive telemetry system for large-scale cloud networks

We present Zoonet, a proactive virtual network telemetry system for multi-tenant clouds. The requirements are to (1) cover hyper-scale virtual networks with millions of tenants and millions of VMs for top tenants; (2) handle frequent virtual topology changes due to tenants' configuration through flexible APIs; (3) adapt to heterogeneous middleboxes along the probing paths; (4) achieve VM-to-VM telemetry without breaking tenant privacy; (5) differentiate virtual and physical network problems. We argue existing physical network telemetry solutions fail to satisfy our needs due to either incomplete telemetry coverage or outrageous telemetry overhead. Zoonet sets an ambitious goal to provide VM-to-VM hop-by-hop telemetry for each tenant, which is achieved based on self-developed, customizable middleboxes via hundreds of person-months under close team collaboration. At the data plane, Zoonet defines an elegant generalization of ping and traceroute, but made to work on multi-tenant clouds with heterogeneous middleboxes. At the control plane, Zoonet conducts substantial probing path pruning and update batch processing to lessen the overhead. Zoonet has been deployed in Alibaba Cloud for over two years, covering tens of cloud regions, hundreds of thousands of servers. We become increasingly reliant on Zoonet as it reduces 86% of the personnel engaged in troubleshooting.
Exact 3D Path Generation via 3D Cam-Linkage Mechanisms

Exact 3D path generation is a fundamental problem of designing a mechanism to make a point exactly move along a prescribed 3D path, driven by a single actuator. Existing mechanisms are insufficient to address this problem. Planar linkages and their combinations with gears and/or plate cams can only generate 2D paths while 1-DOF spatial linkages can only generate 3D paths with rather simple shapes. In this paper, we present a new 3D cam-linkage mechanism, consisting of two 3D cams and five links, for exactly generating a continuous 3D path. To design a 3D cam-linkage mechanism, we first model a 3-DOF 5-bar spatial linkage to exactly generate a prescribed 3D path and then reduce the spatial linkage's DOFs from 3 to 1 by composing the linkage with two 3D cam-follower mechanisms. Our computational approach optimizes the 3D cam-linkage mechanism's topology and geometry to minimize the mechanism's total weight while ensuring smooth, collision-free, and singularity-free motion. We show that our 3D cam-linkage mechanism is able to exactly generate a continuous 3D path with arbitrary shape and a finite number of C0 points, evaluate the mechanism's kinematic performance with 3D printed prototypes, and demonstrate that the mechanism can be generalized for exact 3D motion generation.
Position-Based Surface Tension Flow

This paper presents a novel approach to simulating surface tension flow within a position-based dynamics (PBD) framework. We enhance the conventional PBD fluid method in terms of its surface representation and constraint enforcement to furnish support for the simulation of interfacial phenomena driven by strong surface tension and contact dynamics. The key component of our framework is an on-the-fly local meshing algorithm to build the local geometry around each surface particle. Based on this local mesh structure, we devise novel surface constraints that can be integrated seamlessly into a PBD framework to model strong surface tension effects. We demonstrate the efficacy of our approach by simulating a multitude of surface tension flow examples exhibiting intricate interfacial dynamics of films and drops, which were all infeasible for a traditional PBD method.
What is the speed boundary between patting and slapping by a robot?: Investigating perceptions toward robot-robot interaction

Such multiple agent interactions as robot-robot interactions are one effective approach to indirectly provide information, unlike direct interactions between people and agents. Several studies reported the effectiveness of this approach and developed conversational mechanisms for robot-robot interaction, although their physical interaction design for robot-robot interaction remains relatively less focused. This study concentrated on the effects of speed in touching behaviors between robots, because people may perceive the relationships shared between robots differently due to various motion speeds even though the motion is identical. Therefore, we conducted two web-survey experiments to investigate the perceptions of a robot's touching motion and how the relationship between two robots was perceived when a robot touched another at different speeds. The first experiment showed two peak speeds where people perceived a robot's touch as patting (friendly touch) or slapping (aggressive touch). The second experiment results showed similar peak speeds where people perceived the relationships between robots as positive or negative to patting or slapping behaviors. We believe that knowledge about the relationships between motion speeds and perceived friendliness between robots will contribute to design physical interaction between robots.
Moral Hazard Incentive Strategies of Dual-channel Supply Chain under Service Free-riding Effect

This paper constructed a dual channel supply chain including online and offline channels. We investigated the manufacturer's incentive strategies when dealing with moral hazard from the retailer, considering the online store can free ride the experience services of the offline store, and consumers pay different attention to experience services. We compared the decisions of the retailer and the manufacturer when information is asymmetric and symmetric (moral hazard exists). It is found that in the presence of moral hazard, the retailer can get positive service compensation and lower wholesale price if high consumer valuation is realized, while she can only get negative service compensation and higher wholesale price if low-state valuation is achieved. It is more possible to realize a high consumer valuation if the retailer makes a positive effort. Under the condition of full information, the service compensation offered to the retailer is independent of the realized experience utilities. When the proportion of the consumers who is attentive to experience services is high enough, the stronger the free-riding effect, the higher the incentive cost the manufacturer needs to pay. That is, the manufacturer can adopt higher service compensation to avoid moral hazard.
OutRAN: co-optimizing for flow completion time in radio access network

Traffic from interactive applications demanding low latency has become dominant in cellular networks. However, existing schedulers of cellular network base stations fall short in delivering low latency when prior information (i.e., dedicated Quality of Service (QoS)) is unavailable; they become service agnostic and perform towards maximizing the radio resource utilization or user fairness. We identify a new opportunity of providing a better latency for those latency-sensitive traffic flows by additionally taking the Flow Completion Time (FCT) into account in downlink scheduling at the base stations. However, the key challenges are 1) it can bring a severe cost in optimization metrics of the existing scheduler and 2) it should work without prior knowledge of the traffic. To this end, we present OutRAN, a practical flow scheduler designed for Radio Access Network that co-optimizes the FCT and optimization objectives of the cellular scheduler. The resulting system does not require prior information. Through simulation and over-the-air evaluation, we demonstrate that OutRAN outperforms the legacy LTE/5G schedulers in FCT, which leads to the reduction in webpage load time of Android phones.
Application of Big Data Technology in Tax Collection and Management and Tax Business Environment

In the era of big data, data has become another factor of production after labor, capital, land, knowledge, technology and management. With the continuous improvement of the level of informatization, data has been widely used in tax collection and management and tax business. With the help of highly developed information technology and the use of various information systems, it can greatly promote the efficiency of tax management and work quality; Work brings challenges. This paper studies the role of big data in tax collection and management and the improvement of the tax business environment. The research results show that big data tax collection and management has effectively improved the tax business environment: on the one hand, big data tax collection and management can achieve panoramic monitoring of tax sources, combat tax evasion and tax evasion, and significantly improve corporate tax compliance by mastering massive financial and tax data and using big data technology. On the other hand, the big data of tax collection and management reduces taxpayers’ tax costs through online tax collection, and realizes the “policy discoverer” through the intelligent retrieval and push system of preferential tax policies. At the same time, the big data of tax collection and management can reduce the cost of tax declaration through online tax collection, and realize the "policy finder" through the intelligent search and push system of preferential tax policies, so as to improve the execution of preferential tax policies. The research results of this paper provide theoretical support and empirical basis for the continuous improvement of tax informatization construction.
Electronic Circuits made of 2D Materials

M. Lanza Materials Science and Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900, Saudi Arabia E-mail: mario.lanza@kaust.edu. sa I. Radu Corporate Research Taiwan Semiconductor Manufacturing Company (TSMC) Hsinchu, Taiwan The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adma.202207843.
PTEN deficiency exposes a requirement for an ARF GTPase module in integrin-dependent invasion in ovarian cancer

Dysregulation of the PI3K/AKT pathway is a common occurrence in ovarian carcinomas. Loss of the tumour suppressor PTEN in high-grade serous ovarian carcinoma (HGSOC) is associated with a patient subgroup with poor prognosis. The cellular mechanisms of how PTEN loss contributes to HGSOC are largely unknown. We utilise long-term time-lapse imaging of HGSOC spheroids coupled to a machine learning approach to classify the phenotype of PTEN loss. PTEN deficiency does not affect proliferation but rather induces PI(3,4,5)P3-rich and -dependent membrane protrusions into the extracellular matrix (ECM), resulting in a collective invasion phenotype. We identify the small GTPase ARF6 as a crucial vulnerability upon PTEN loss. Through a functional proteomic CRISPR screen of ARF6 interactors, we identify the ARF GTPase-activating protein (GAP) AGAP1 and the ECM receptor β1-integrin (ITGB1) as key ARF6 interactors regulating the PTEN loss-associated invasion phenotype. ARF6 functions to promote invasion by controlling the recycling of internalised, active β1-integrin complexes to maintain invasive activity into the ECM. The expression of the ARF6-centred complex in HGSOC patients is inversely associated with outcome, allowing identification of patient groups with improved versus poor outcome. ARF6 may represent a new therapeutic vulnerability in PTEN- depleted HGSOC tumours.
Intrinsic macroscale oscillatory modes driving long range functional connectivity detected with ultrafast fMRI

Spontaneous fluctuations in functional Magnetic Resonance Imaging (fMRI) signals correlate across distant brain areas, shaping functionally relevant intrinsic networks. However, the generative mechanism of fMRI signal correlations - and in particular their link with locally-detected ultra-slow oscillations - remain unclear. To investigate this link, we record ultrafast ultrahigh field fMRI signals (9.4 Tesla, temporal resolution = 38 milliseconds) from rat brains across three anesthesia conditions. Power at frequencies extending up to 0.3 Hz is detected consistently across rat brains, and is modulated by anesthesia level. Principal component analysis reveals a repertoire of modes, in which transient oscillations organize with fixed phase relationships across distinct cortical and subcortical structures. Oscillatory modes are found to vary between conditions, resonating at faster frequencies under medetomidine sedation and reducing both in number, frequency, and duration with the addition of isoflurane. Peaking in power within clear anatomical boundaries, these oscillatory modes point to an emergent systemic property, questioning current assumptions regarding the local origin of oscillations detected in fMRI and providing novel insights into the organizing principles underpinning spontaneous long-range functional connectivity. One Sentence Summary Oscillations in fMRI signals organize in stationary wave patterns driving condition-specific long-range correlations across brain structures
Sustained Modulation of Deep Brain Circuits with Focused Ultrasonic Waves

Transcranial focused ultrasound has the potential to noninvasively and systematically modulate deep brain circuits and impart sustained, neuroplastic effects in awake subjects. The intersection of these properties is critical for effective treatments of brain disorders, yet remains to be shown. Harnessing the full potential of transcranial ultrasound, we delivered 30-second stimuli into deep brain targets (left/right lateral geniculate nucleus) of non-human primates while they performed a visual discrimination task. This brief stimulation induced sustained and target-specific behavioral preference that persisted up to 15 minutes following the ultrasound offset. The polarity of the behavioral and neural effects suggested that ultrasound excited the stimulated circuits. The ultrasound was delivered into the deep brain daily for a period of more than 6 months, which enabled us to evaluate the safety of longterm stimulation. There were no detrimental effects on the animals’ discrimination accuracy over the course of this stimulation regimen. This study demonstrates ultrasound’s capacity to condition deep brain circuits in a safe and treatment-relevant manner in awake subjects, and provides a basis for effective and safe translations into humans. Highlights Transcranial ultrasound induces effective and sustained modulation of deep brain circuits. The deep brain modulation biases choice behavior of non-human primates. The deep brain modulation produces sustained elevation of high gamma activity. The stimulation, applied daily for several months, is safe.
Characterization of the functional and transcriptomic effects of pro-inflammatory cytokines on human EndoC-βH5 beta cells

Objective EndoC-βH5 is a newly established human beta-cell model which may be superior to previous models of native human beta cells. Exposure of beta cells to proinflammatory cytokines is a widely used in vitro model of immune-mediated beta-cell failure in type 1 diabetes and we therefore performed an in-depth characterisation of the effects of cytokines on EndoC-βH5 cells. Methods The sensitivity profile of EndoC-βH5 cells to the toxic effects of the pro-inflammatory cytokines interleukin-1β (IL-1β), interferon γ (IFNγ) and tumour necrosis factor-α (TNFα) was examined in titration and time-course experiments. Cell death was evaluated by caspase 3/7 activity, cytotoxicity, viability, TUNEL assay and immunoblotting. Mitochondrial function was evaluated by extracellular flux technology. Activation of signalling pathways and major histocompatibility complex (MHC) class I expression were examined by immunoblotting, immunofluorescence, and real-time quantitative PCR (qPCR). Glucose-stimulated insulin secretion (GSIS) and cytokine-induced chemokine secretion were measured by ELISA and Meso Scale Discovery multiplexing electrochemiluminescence, respectively. Global gene expression was characterised by stranded RNA sequencing. Results Cytokines increased caspase activity and cytotoxicity in EndoC-βH5 cells in a time- and dose-dependent manner. The proapoptotic effect of cytokines was primarily driven by IFNγ. Cytokine exposure caused impaired mitochondrial function, diminished GSIS, and induced secretion of chemokines. At the signalling level, cytokines increased the phosphorylation of signal transducer and activator of transcription 1 (STAT1) but not c-jun N-terminal kinase (JNK) and did not cause degradation of nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor α (IκBα). MHC class I was induced by cytokines. Cytokine exposure caused significant changes to the EndoC-βH5 transcriptome including upregulation of HLA genes, endoplasmic reticulum stress markers, and non-coding RNAs. Among the differentially expressed genes were several type 1 diabetes risk genes. Conclusions Our study provides detailed insight into the functional and transcriptomic effects of cytokines on EndoC-βH5 cells. This knowledge will be helpful for future investigations studying cytokine effects in this cell model.
ARCHE: AN ADVANCED FLEXIBLE TOOL FOR HIGH-THROUPUT ANNOTATION OF FUNCTIONS ON MICROBIAL CONTIGS

The growing amount of genomic data has prompted a need for less demanding and user friendly functional annotators. At the present, it’s hard to find a pipeline for the annotation of multiple functional data, such as both enzyme commission numbers (E.C.) and orthologous identifiers (KO and eggNOG), protein names, gene names, alternative names, and descriptions. In this work, we provide a new solution which combines different algorithms (BLAST, DIAMOND, HMMER3) and databases (UniprotKB, KOfam, NCBIFAMs, TIGRFAMs, and PFAM), and also overcome data download challenges. The software framework, Arche, herein demonstrated competitive results over Escherichia coli K12 genome when compared to other annotators. Finally, Arche provides an analysis pipeline that can accommodate advanced tools in a unique order, creating several advantages regarding to other commonly used annotators.
Large-Scale Structures in the Interstellar Medium

Large-scale ordered structures in the interstellar medium (ISM) are commonly explained as a manifestation of the various instabilities inherent to the motion of partially ionized, magnetized interstellar gas. We examined the process of creation of large-scale coherent eddy structures in the ISM characterized by the existence of fully developed small-scale turbulence with nonzero values of the hydrodynamic and magnetic helicities. The instability analysis shows that in such media large-scale ordered structures with characteristic scale l ~ 1-100 pc are generated. The generation coefficient of large-scale structures is determined by both the value of the hydrodynamic helicity and the combined influence of the drag force and magnetic helicity.
Solving Nonconvex Optimal Control Problems by Convex Optimization

Motivated by aerospace applications, this paper presents a methodology to use second-order cone programming to solve nonconvex optimal control problems. The nonconvexity arises from the presence of concave state inequality constraints and nonlinear terminal equality constraints. The development relies on a solution paradigm, in which the concave inequality constraints are approximated by successive linearization. Analysis is performed to establish the guaranteed satisfaction of the original inequality constraints, the existence of the successive solutions, and the equivalence of the solution of the original problem to the converged successive solution. These results lead to a rigorous proof of the convergence of the successive solutions under appropriate conditions as well as nonconservativeness of the converged solution. The nonlinear equality constraints are treated in a two-step procedure in which the constraints are first approximated by first-order expansions, then compensated by second-order correct.
Rainfall Microphysics and Radar Properties: Analysis Methods for Drop Size Spectra

Abstract Analyses are performed of experimental drop size spectra to explore the relationships among integral parameters for rain. The data used in this work were acquired with an airborne optical 2D precipitation probe in TOGA COARE during a 4-month period in 1992–93. It is assumed that the experimental size spectra can be described by a gamma drop size distribution (DSD) of the form N(D) = N0Dμ exp(−ΛD) involving three parameters (N0, μ, Λ), which are determined using a new method of truncated moments. The method allows for truncation of the DSD at the large-diameter end of the spectrum due in part to instrumental effects and also in part to the trajectory of the aircraft through a rain streamer that has been sorted by wind shear. An effect analogous to truncation can occur at the small-diameter end of the size spectrum due to evaporation. However, truncation of the spectrum at the small-diameter end is not considered in this work. It is found that spectra with small space and timescales display conside.
Erbium luminescence imaging of infrared surface plasmon polaritons

We demonstrate a new technique to spatially map the propagation and damping of infrared surface plasmon polaritons (SPPs) on metal films using optically active erbium ions as a probe of the SPP field. The bound SPP mode propagating along the Ag/glass interface of a 96nm thick Ag film on glass is excited by illuminating a subwavelength hole array in the metal with 1. 49μm light. By imaging the 1. 53μm photoluminescence of Er ions positioned in the glass at a distance of 60nm from the Ag/glass interface in a confocal microscope, a SPP beam was observed to propagate along a broad stripe waveguide, with a characteristic propagation length of 76μm. This technique provides a useful tool to study the characteristics of SPP modes at metal-dielectric interfaces in a wide range of geometries.
Benchmark of Simplified Formulations for the Electrical Conductivity of Non‐Ideal Plasmas

We discuss simplified formulations for the electrical conductivity [1] and compare them with experimental results of various expanded metals recently published [2]. We use formulations designed for fully ionized hydrogen in a broader range of non‐fully ionized materials of various atomic number through the use of an effective coupling parameter based on estimations of the ionization. The ionizations are deduced from average‐atom calculations and compared with faster Thomas‐Fermi‐Dirac estimations. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
MIPNet

We present MIPNet, a novel approach for SVBRDF mipmapping which preserves material appearance under varying view distances and lighting conditions. As in classical mipmapping, our method explicitly encodes the multiscale appearance of materials in a SVBRDF mipmap pyramid. To do so, we use a tensor-based representation, coping with gradient-based optimization, for encoding anisotropy which is compatible with existing real-time rendering engines. Instead of relying on a simple texture patch average for each channel independently, we propose a cascaded architecture of multilayer perceptrons to approximate the material appearance using only the fixed material channels. Our neural model learns simple mipmapping filters using a differentiable rendering pipeline based on a rendering loss and is able to transfer signal from normal to anisotropic roughness. As a result, we obtain a drop-in replacement for standard material mipmapping, offering a significant improvement in appearance preservation while still boiling down to a single per-pixel mipmap texture fetch. We report extensive experiments on two distinct BRDF models.