Miracle-dz/UniFAR-FTUs huggingface dataset:
PEO-Store: Practical and Economical Oblivious Store with Peer-to-Peer Delegation

The growing popularity of cloud storage has brought attention to critical need for preventing information leakage from cloud access patterns. To this end, recent eﬀorts have extended Oblivious RAM (ORAM) to the cloud environment in the form of Oblivious Store. However, its impracticality due to the use of probability encryption with fake accesses to obfuscate the access pattern, as well as the security requirements of conventional obliviousness designs, which hinder cloud interests in improving storage utilization by removing redundant data among cross-users, limit its eﬀectiveness. Thus, we propose a practical Oblivious Store, PEO-Store, which integrates the obliviousness property into the cloud while removing redundancy without compromising security. Unlike conventional schemes, PEO-Store randomly selects a delegate for each client to communicate with the cloud, breaking the mapping link between a valid access pattern sequence and a speciﬁc client. Each client encrypts their data and shares it with selected delegates, who act as intermediaries with the cloud provider. This design leverages non-interactive zero-knowledge-based redundancy detection, discrete logarithm problem-based key sharing, and secure time-based delivery proof to protect access pattern privacy and accurately identify and remove redundancy in the cloud. The theoretical proof demonstrates that the probability of identifying the valid access pattern with a speciﬁc user is negligible in our design. Experimental results show that PEO-Store outperforms state-of-the-art methods, achieving an average throughput of up to 3 times faster and saving 74% of storage space.
Practical Security Analysis of Zero-Knowledge Proof Circuits

As privacy-sensitive applications based on zero-knowledge proofs (ZKPs) gain increasing traction, there is a pressing need to detect vulnerabilities in ZKP circuits. This paper studies common vulnerabilities in Circom (the most popular domain-specific language for ZKP circuits) and describes a static analysis framework for detecting these vulnerabilities. Our technique operates over an abstraction called the circuit dependence graph (CDG) that captures key properties of the circuit and allows expressing semantic vulnerability patterns as queries over the CDG abstraction. We have implemented 9 different detectors using this framework and perform an experimental evaluation on over 258 circuits from popular Circom projects on Github. According to our evaluation, these detectors can identify vulnerabilities, including previously-unknown ones, with high precision and recall.
Hardware Root-of-Trust implementations in Trusted Execution Environments

Hardware-based Root of Trust (HRT) is considered the gold standard for bootstrapping trust in secure computing. This paper analyzes HRT implementations across state-of-the-art TEEs and diﬀerentiates HRT implementation across two dimensions: 1) Security Properties & Threats and 2) Hardware Capabilities. Later, this work analyzes and compares 1) Intel SGX, 2) ARM TrustZone, 3) NXP Trust Architecture, 4) AMD SEV, 5) Microsoft Pluton, and 6) Apple T2 HRTs in terms of threats, security properties, and capabilities.
SoK: Privacy-Enhancing Technologies in Finance

Financial applications have historically required strong security guarantees. These can be achieved in a digital world via cryptographic tools but have traditionally been employed to provide authenticity and privacy for data exchanged between clients and financial institutions over insecure networks ( e.g. the Internet). However, the recent advent of cryptocurrencies and smart contract platforms, based on blockchains, allowed financial transactions to be carried out over a public ledger, instead of keeping such transactions exclusive to private institutions. This introduced a new challenge: Allowing any third party to verify the validity of financial operations by means of public records on a blockchain, while keeping sensitive data private. Advanced cryptographic techniques such as Zero Knowledge (ZK) proofs rose to prominence as a solution to this challenge, allowing for the owner of sensitive information ( e.g. the identities of users involved in an operation) to provide unforgeable evidence that a certain operation has been correctly executed without revealing said sensitive data. Moreover, once the Fintech community discovered the power of such advanced techniques, it also became clear that performing arbitrary computation on private data by means of secure Multiparty Computation (MPC), and related techniques like Fully Homomorphic Encryption (FHE), would allow more powerful financial applications, also in traditional finance, involving sensitive data from multiple sources. In this survey, we present an overview of the main Privacy-Enhancing Technologies (PETs) available in the state of the art of current advanced cryptographic research and how they can be used to address challenges in both traditional and decentralized finance. In particular, we consider the following classes of applications: 1. Identity Management, KYC &
Faithful Simulation of Randomized BFT Protocols on Block DAGs

Byzantine Fault-Tolerant (BFT) protocols that are based on Directed Acyclic Graphs (DAGs) are attractive due to their many advantages in asynchronous blockchain systems. These DAG-based protocols can be viewed as a simulation of some BFT protocol on a DAG. Many DAG-based BFT protocols rely on randomization, since they are used for agreement and ordering of transactions, which cannot be achieved deterministically in asynchronous systems. Randomization is achieved either through local sources of randomness
Recursive-batch estimation of motion and structure from monocular image sequences

Abstract This paper addresses the issue of optimal motion and structure estimation from monocular image sequences of a rigid scene. The new method has the following characteristics: (1) the dimension of the search space in the nonlinear optimization is drastically reduced by exploiting the relationship between structure and motion parameters; (2) the degree of reliability of the observations and estimates is effectively taken into account; (3) the proposed formulation allows arbitrary interframe motion; (4) the information about the structure of the scene, acquired from previous images, is systematically integrated into the new estimations; (5) the integration of multiple views using this method gives a large 2.5D visual map, much larger than that covered by any single view. It is shown also that the scale factor associated with any two consecutive images in a monocular sequence is determined by the scale factor of the first two images. Our simulation results and experiments with long image sequences of real world scenes indicate that the optimization method developed in this paper not only greatly reduces the computational complexity but also substantially improves the motion and structure estimates over those produced by the linear algorithms.
On the distribution function of H Atoms in the problem of the solar wind interaction with the local interstellar medium

This paper is devoted to the analysis of the models of the solar wind interaction with the local interstellar medium (LISM) self-consistently taking into account mutual influence of plasma (electrons and protons) and neutral (H atoms) components of the LISM. The axisymmetric interaction model of Baranov and Malama [1993], that used the kinetic description of H atoms motion together with the hydrodynamic approximation for the plasma component, showed that the distribution functions of the all H atom populations are essentially not Maxwellian. The hydrodynamic model by Zank et al. [1996] is based on the Maxwellian distribution functions of the LISM and solar wind hydrogen atoms. The comparisons of the results obtained on the basis of the kinetic model by Baranov and Malama [1993] and multifluid model by Zank et al. [1996] show that the distributions of H atom parameters have large quantitative as well as qualitative distinctions. A number of theoretical predictions and relevant, experimental data are analyzed.
A Novel Graph Construction Method Based on Locality Sensitive Histogram for Locality Preserving Projections

This paper presents a novel construction method of neighbor graph based on locality sensitive histogram for Locality Preserving Projections (LPP), which is called LSH Graph Construction. Unlike the conventional construction method of neighbor graph that vectorizes the original data set to compute the k-nearest neighbor graph, the LSH graph construction method which we proposed is acting on 2D image matrixes directly. Firstly, we compute each sample’s locality sensitive histogram, so that each sample can be easily divided into multiple overlapping regions. Then we construct the samples’ neighbor graph basing on corresponding region-to-region matching. Our proposed LSH Graph Construction method have the following two advantage: it can preserve samples’ intrinsic structural information and is insensitive to illumination and pose variation in some extent. We apply LSH Graph Construction into the famous dimensionality algorithm: LPP to develope a new algorithm called LSHG-LPP. Experiments on two wellknown face databases (Yale and ORL face databases) demonstrate that the proposed method outperforms LPP.
Dual-frequency triangular microstrip antenna with a shorting pin

This paper presents a novel design of triangular microstrip antenna with dual-frequency operation. In this design the microstrip patch is short-circuited using a shorting pin and fed by a single probe feed. By varying the shorting pin position in the microstrip patch, such a design can provide a large tunable frequency ratio of about 2.5-4.9 for the two operating frequencies. Experimental results for operating at frequencies of 464 and 2276 MHz are presented and discussed.
S1759078722000095jrv 156..182

As the demand for high data rates is increasing day by day, fifth-generation (5G) becomes the leading-edge technology in wireless communications. The main objectives of the 5G communication system are to enhance the data rates (up to 20 Gbps) and capacity, ultra-low latency (1 ms), high reliability, great flexibility, and enhance device to device communication. The mentioned objectives lead to the hunting of the millimeter-wave frequency range which lies from 30 to 300 GHz for 5G wireless communications. To design such high capacity, low latency, and flexible systems, antenna design is one of the crucial parts. In this paper, a survey is presented on various antenna designs with their fabrication on different types of substrates such as Rogers RT/duroid 5880, Rogers RO4003C, Taconic TLY-5, etc., at different 5G frequency bands. The different configurations of antennas that covered antenna arrays, multiple-input multiple-output (MIMO) antennas, phased antennas, and beamforming antennas are discussed in detail with their applications. The design of MIMO antennas in the 5G frequency band occupied less space so mutual coupling reduction techniques are required for maintaining the required gain, efficiency, and isolation. This paper is also focused on the mutual coupling reduction techniques and diversity in MIMO antennas.
TGF-β in wound repair and scarring

Wound healing is a multi-step process which is the result of complex interactions of cells present in the injured tissue with cellular and soluble blood constituents (1). These interactions are governed by the action of growth factors, chemokines, and hormones. Cellular responses as well as the action of soluble mediators are modulated by the extracellular matrix (ECM) present in the wound area. Wound repair proceeds through a sequence of different stages, each of them being fundamentally influenced by the TGF-β family members, TGF-β1, 2, 3, or activin (2-4). Among the first responses to injury are activation of platelets and the initiation of blood coagulation, whereby platelets are a major source of TGF-β1 in the early stages of wound repair (5, 6). The release and activation of platelet TGF-β1 probably contributes to the initiation of early cellular responses, such as the chemotactic recruitment of inflammatory cells (7) and new blood vessels (8) into the wound area. In contrast, TGF-β1 delays re-epithelialization when added to organotypic cultures in vitro (9) or when overexpressed in the epidermis in vivo (10). This inhibitory effect of TGF-β signaling in keratinocytes has been confirmed in vivo by transgenic studies demonstrating accelerated re-epithelialization in mice deficient in TGF-β1 (11), in the signaling keratinocyte type II TGF-β receptor (12), or in the intracellular TGF-β signal transducer, Smad3 (13). At later stages of normal wound repair, TGF-β1 is a major inducer of connective tissue production and myofibroblast activity. Consequently, TGF-β1 activity promotes wound contraction and enhances wound breaking strength (14). In addition, TGF-β1 stimulates scar formation and tissue remodeling and may also be involved in pathologic healing responses such as hypertrophic scarring and fibrosis (15, 16). Impaired wound healing states (e.g. venous and diabetic ulcers or glucocorticoid-induced wound healing defects) are characterized by reduced expression of TGF-β1 and the type II © 2004 Schattauer GmbH, Stuttgart
A Method for Extracting Postevent Storm Tracks

AbstractAlthough existing algorithms for storm tracking have been designed to operate in real time, they are also commonly used to do postevent data analysis and research. Real-time algorithms cannot use information on the subsequent positions of a storm because it is not available at the time that associations between frames are made, but postevent analysis is not similarly constrained. Therefore, it should be possible to obtain better tracks for postevent analysis than those that a real-time algorithm is capable of producing. In this paper, a statistical procedure for determining storm tracks from a set of identified storm cells over time is described. It is found that this procedure results in fewer, longer-lived tracks at the potential cost of a small increase in positional error.
Development and application of an objective storm severity measure for the Northeast Atlantic region

An objective index for the estimation of storm severity has been developed, validated and applied to both reanalysis data and an AOGCM simulation for the Northeast Atlantic region. The index is based on the exceedance of local thresholds of the daily maximum wind speed. Positive trends for both the severity of storms during the historic ERA40 period (1960-2000), and under anthropogenic climate change (ACC) conditions (SRES A1B and A2) are identified. Additionally an increase in the spatial extent of storms is diagnosed, amounting up to about 10 % between present day and the scenario climate. Two types of the index are introduced: One area integrated measure for the investigation domain of 50°W to 20°E, 45°N to 70°N, called ASSI (Area Storm Severity Index), per day; and one event integrated index, called ESSI (Event Storm Severity Index), per storm event. ASSI and ESSI clearly identify extreme "cyclone bombs" under ACC conditions, which exceed the range found in observed (ERA40) and simulated data for the recent climate. ASSI and ESSI identify an increase in the severity of storms for the Northeast Atlantic and western Central Europe under ACC conditions. The index can easily be calculated for large data sets, and is thus well applicable to multi-model ensemble simulations in order to objectively estimate climate change signals and related measures of uncertainty. Reasons for the increase in severity could be seen mainly in the occurrence of higher wind speeds, and in larger areas affected by storms. These larger areas result from longer tracks combined with a common broadening along the path.
A process-based approach to dynamic social network analysis using Enron e-mail

Common methods of social network analysis (SNA) emphasize the static analysis of role relationships: the roles of different actors are understood based on patterns of transactions conducted over stationary channels that connect them.1–3 Semantic methods for analyzing a stable corpus of transactions dominate the techniques for message classification. Such stationary analyses are poorly suited to identifying behaviors that are potentially sparse but well-coordinated (synchronous). Malevolent organizations such as terrorist cells may use a variety of techniques to escape detection, such as cloaking language and embedding communications into otherwise innocuous background traffic. The sheer quantity of natural interactions of large numbers of actors in an active social network can be computationally daunting. In this work, we move beyond traditional static methods of SNA to develop a set of dynamic process models that encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS)4 to the identification and tracking of dynamic processes. We are working on a process-driven approach to dynamic social network analysis (DSNA) based on the idea that a network’s organizational structure, as well as its characteristic messaging patterns, reflect distributed dynamic processes operating on the network. A primary goal in applying a process-driven approach to DSNA is to develop techniques and a general framework that can be applied across multiple languages and domains. The PQS technology developed at Dartmouth College provides an ideal platform for performing such process-based analysis. By exploiting the temporal attributes of the transactions, we are able to distinguish likely threads of conversation using only rudiFigure 1. The Trafen Engine, an implementation of Process Query System (PQS) technology, was used to process Enron e-mail.
Linear arrays with variable interelement spacings

Optimum broadside arrays with constant spacings, i.e., Dolph-Tchebycheff arrays, use relatively many elements and are often difficult to realize in practice due to mutual coupling effects. To overcome these disadvantages a variety of arrays with widely and variably spaced elements have been designed using both analog and digital computer techniques. These arrays all have many fewer elements than Dolph-Tchebycheff arrays with the same beamwidth and sidelobe level. One of the arrays designed has 21 elements and is 76 wavelengths long when used as a broadside array. The 3-db beamwidth is 0.74 degree, the sidelobe level -7.4 db. The array has perfect steerability in a 1.8:1 bandwidth with no interelement spacing smaller than one-half wavelength in this band. A Dolph-Tchebycheff array with the same beamwidth and sidelobe level uses 53 elements, and the steerability is not perfect even at a single frequency.
Deep Level Characterization of Submillimeter-Wave GaAs Schottky Diodes Produced by a Novel In-Situ Electrochemical Process

Various preparation methods used for the fabrication of submillimeter-wave Pt/GaAs Schottky diodes are compared with respect to deep levels present in the diode surface region. In the samples prepared by the standard electron-beam evaporation process, three process-induced deep levels were detected with the concentrations in the range of 1013-1014 cm-3. On the other hand, these levels were very much reduced in the diodes produced by a new in-situ electrochemical technique. This appears to be related to the reported very low noise property of the latter diodes.
A Construction for Partitions Which Avoid Long Arithmetic Progressions

For k ≥2, t ≥2, let W(k, t) denote the least integer m such that in every partition of m consecutive integers into k sets, atleast one set contains an arithmetic progression of t+1 terms. This paper presents a construction which improves the best previously known lower bounds on W(k, t) for small k and large t.
Compact input-reflectionless balanced bandpass filter with flexible bandwidth using three-line coupled structure

本文提出一种基于三线耦合结构的具有灵活带宽的紧凑型平衡式输入无反射带通滤波器。 在差模模式下, 带通响应由三线耦合结构实现, 同时三线耦合结构的输入耦合馈线被输入吸收网络复用。 带通滤波部分和吸收部分实现了良好的融合, 有效地减小了电路尺寸, 并且两部分的带宽独立可控, 进而使得该滤波器的差模响应带宽具有灵活可控的特性。 此外, 首次对两部分的带宽比进行详细分析,以获得通带平坦度与无反射性能的良好折衷。 因此, 该协同设计的输入无反射差模带通响应具有易于优化的特点。 同时, 输入端的吸收网络还实现了宽频带内的共模噪声吸收。 为了验证该设计方法, 设计了一款尺寸为0.52 λ ×0.36 λ 的平衡式输入无反射滤波器, 测量范围为0–7.0 GHz。 测得差模响应的中心频率为2.45 GHz, 3 dB相对带宽为31.4%。 实测和仿真结果展现了良好的一致性, 并且该滤波器具有0.43 dB的低插入损耗、较宽的差模上阻带(超过20 dB的抑制水平至2.72倍频)以及宽带的差模无反射和共模噪声吸收(吸收相对带宽为285.7%)等优点。 A compact input-reflectionless balanced bandpass filter (BPF) with flexible bandwidth (BW) using a three-line coupled structure (TLCS) is presented in this paper. For the differential mode (DM), the TLCS is applied to achieve the bandpass response; meanwhile, the input coupled-feed line of the TLCS is reused in the input absorption network. This design shows a good fusion of the absorptive and BPF sections, effectively reducing the circuit size, and the BWs of the two sections that can be controlled separately result in a flexibly controllable DM response BW of the proposed input-reflectionless balanced BPF. Detailed analyses of the ratio of the two-part BWs have been given for the first time, which is vital for the passband flatness and reflectionless feature. In the codesign of this work, the input-reflectionless DM bandpass response can be optimized easily, while wideband common mode (CM) noise absorption is achieved by the input absorption network. To verify the design method, a prototype with a compact layout (0.52 λ ×0.36 λ ) is designed and measured in the 0–7.0 GHz range. The DM center frequency ( f _0) is 2.45 GHz with a measured 3 dB fractional bandwidth of 31.4%. The simulation and measurement results with good agreement are presented, showing good performance, e.g., low insertion loss (0.43 dB), wide upper stopband for the DM bandpass response (over 20 dB rejection level up to 2.72 f _0), and wideband DM reflectionless and CM noise absorption (fractional absorption bandwidth of 285.7%).
Quantum dots as self-referenced optical fibre temperature probes for luminescent chemical sensors

The use of semiconductor nano-particles as temperature probes in luminescence chemical sensing applications is addressed. Temperature changes the intensity, the peak wavelength and the spectral width of the quantum dots luminescent emission in a linear and reversible way. Results are presented that show the feasibility of implementing a self-referenced intensity-based sensor to perform temperature measurements independent of the optical power level in the sensing system. A resolution of 0.3 °C was achieved. In addition, it is demonstrated that self-referenced temperature measurements at multiple points could be performed using reflection or transmission based optical fibre configurations.
The Hausdorff dimension of self-affine fractals

Abstract If T is a linear transformation on ℝn with singular values α1 ≥ α2 ≥ … ≥ αn, the singular value function øs is defined by where m is the smallest integer greater than or equal to s. Let T1, …, Tk be contractive linear transformations on ℝn. Let where the sum is over all finite sequences (i1, …, ir) with 1 ≤ ij ≤ k. Then for almost all (a1, …, ak) ∈ ℝnk, the unique non-empty compact set F satisfying has Hausdorff dimension min{d, n}. Moreover the ‘box counting’ dimension of F is almost surely equal to this number.
A Multi-Step Reinforcement Learning Algorithm

Reinforcement learning (RL) is a state or action value based machine learning method which approximately solves large-scale Markov Decision Process (MDP) or Semi-Markov Decision Process (SMDP). A multi-step RL algorithm called Sarsa(,k) is proposed, which is a compromised variation of Sarsa and Sarsa(). It is equivalent to Sarsa if k is 1 and is equivalent to Sarsa() if k is infinite. Sarsa(,k) adjust its performance by setting k value. Two forms of Sarsa(,k), forward view Sarsa(,k) and backward view Sarsa(,k), are constructed and proved equivalent in off-line updating.