Miracle-dz/UniFAR-FTUs huggingface dataset:
Blockchain collections

Blockchains are often used as a decentralized mechanism to store and evolve in time data that can be represented as a set of key/value associations. Among the most notable examples of this are cryptocurrencies, which store ledgers of transactions whose application results in a set of associations between public keys and account balances. In order to determine the value associated to a key, or to validate new blocks, nodes are often required to store either a full copy of the ledger (i.e., the complete set of transactions in the blockchain) or at least a full copy of the resulting database (i.e., the set of key/value associations resulting from the application of all the transactions in the ledger). This results in a high storage complexity that usually prevents lightweight nodes (like mobile phones or web applications) from using the blockchain without the aid of trusted third parties. In order to address this problem, we introduce collections , a Merkle-tree based key/value store. Collections can be used to securely store a set of key/value associations (or records ) on one or more untrusted servers. From the set of records in a collection, an O (1) -size state can be eﬃciently computed. Nodes holding a copy of the collection’s state can query the untrusted server(s) for records, and securely verify their responses. Moreover, nodes holding a copy of an old state of the collection can, provided with an update , verify its applicability and autonomously and eﬃciently compute the new state of the collection, resulting from the application of the update. In this report, we provide an overview on how collections are designed, provide arguments for their security and describe a blockchain architecture with total space complexity quasilinear in the number of records. We then brieﬂy discuss and benchmark a full Go collections implementation, that we release as an easy-to-use, open-source library. Finally, we propose to use collections to develop a decentralized, highly eﬃcient database optimized for low-energy, high-uptime devices.
and on the Social Origins of the Artist

Vere Gordon Childe’s theory of craft specialisation was an important influence on Arnold Hauser’s book The Social History of Art , published 1951. Childe’s Marxist interpretation of prehistory enabled Hauser to establish a material foundation for the occupation of the artist in Western art history. However, Hauser’s effort to construct a progressive basis for artistic labour was complicated by art’s ancient connections to religion and superstition. While the artist’s social position and class loyalties were ambiguous in Childe’s accounts of early civilisations, Hauser consigned artists to the lower echelons of society. This relegation did not imply that Hauser had a low regard for artistic skills. Quite the opposite, the artist’s inferior social status enabled Hauser to distance artists from the ruling class, and consequently, to separate artistic handiwork from the dominant ideology that works of art manifested.
Radiation Structures and Numerical Methods

The chapter discusses analytical techniques for antennas and explains their appropriate use. Starting with radiation from electric and magnetic currents and the related Greens functions, they are combined into Huygens sources of geometric optics (GO). Physical optics (PO) combines boundary conditions with Green's functions. The reaction theorem leads to moment methods using approximate currents instead of the iterative PO. Finite difference time domain (FDTD) solves Maxwell's equations in the time domain. Geometric theory of diffraction (GTD) adds the scattering from edges and curved surfaces to extend GO to finite frequencies.
HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning

Effective physical database design tuning requires selection of several physical design structures (PDS), such as indices and materialised views, whose combination influences overall system performance in a non-linear manner. While the simplicity of combining the results of iterative searches for individual PDSs may be appealing, such a greedy approach may yield vastly suboptimal results compared to an integrated search. We propose a new self-driving approach (HMAB) based on hierarchical multi-armed bandit learners, which can work in an integrated space of multiple PDS while avoiding the full cost of combinatorial search. HMAB eschews the optimiser cost misestimates by direct performance observations through a strategic exploration, while carefully leveraging its knowledge to prune the less useful exploration paths. As an added advantage, HMAB comes with a provable guarantee on its expected performance. To the best of our knowledge, this is the first learned system to tune both indices and materialised views in an integrated manner. We find that our solution enjoys superior empirical performance relative to state-of-the-art commercial physical database design tools that search over the integrated space of materialised views and indices. Specifically, HMAB achieves up to 96% performance gain over a state-of-the-art commercial physical database design tool when running industrial benchmarks.
The expanded Lagrangian system for constrained optimization problems

Smooth penalty functions can be combined with numerical continuation and bifurcation techniques to produce a class of robust and potentially fast algorithms for constrained optimization problems. The key to the development of these algorithms is an expanded Lagrangian system which is derived and analyzed in this work. This parametrized system of nonlinear equations contains the penalty path as a solution, provides a smooth path into the first-order necessary conditions, and sometimes yields a method for finding multiple optima. Furthermore, the inevitable ill-conditioning present in a sequential optimization algorithm is removed for three and essentially only three smooth penalty functions: the quadratic penalty function for equality constraints, the logarithmic barrier function (an interior method), and the quadratic loss function (an exterior method) for inequality constraints. Preliminary test results for several nontrivial test problems are included to demonstrate the robustness, efficiency and potent.
The Statistical Characteristics of Static Friction

Friction is one of the fundamental issues in physics, mechanics and material science with many practical applications. However, the understanding of macroscopic friction phenomena from microscopic aspect is still on the way. In this paper, molecular dynamics simulations are performed to investigate the static friction between two planar crystal surfaces. The friction force experienced by each atom is tracked and the statistical characteristics of atomic friction force are illuminated. More importantly, the influences of normal load and temperature on the statistical features are generalized. This study provides a new insight on the micro-states of friction.
Identi ﬁ cation of an N6-methyladenosine-mediated positive feedback loop that promotes Epstein – Barr virus infection

N6-methyladenosine (m 6 A) is among the most abundant mRNA modi ﬁ cations, particularly in eukaryotes, and is found in mammals, plants, and even some viruses. Although essential for the regulation of many biological processes, the exact role of m 6 A modi ﬁ cation in virus – host interaction remains largely unknown. Here, using m 6 A -immunoprecipitation and sequencing, we ﬁ nd that Epstein – Barr virus (EBV) infection decreases the m 6 A modi ﬁ cation of transcriptional factor KLF4 mRNA and subsequently increases its protein level. Mecha-nistically, EBV immediate-early protein BZLF1 interacts with the promoter of m 6 A methyltransferase METTL3, inhibiting its expression. Subsequently, the decrease of METTL3 reduces the level of KLF4 mRNA m 6 A modi ﬁ cation, preventing its decay by the m 6 A protein YTHDF2. KLF4 upregulated EBV infection of nasopharyngeal epithelial cells. our results suggest the existence of a positive between via m 6 and this feedback acts to facilitate viral This mechanism contains multiple potential targets for controlling viral infectious for 24 h. The BZLF1 promoter activity was determined by dividing the fold change of the ﬁ re ﬂ y luciferase value with the Renilla luciferase value, and the mean value of the BZLF1 promoter activity in the vector control cells was de ﬁ ned as 1. The protein levels of KLF4, METTL3, and YTHDF2 were analyzed by western blotting using an anti-Flag antibody. Beta-actin was used as loading control. H , a working model for the crosstalk between EBV and host cells. After EBV acute infection, the EBV IE gene BZLF1 was immediately expressed and suppressed the expression of the m 6 A modi ﬁ cation writer METTL3 to regulate cellular m 6 A levels. Lower expression of METTL3 could increase the RNA
Precise determination of critical points of topological phase transitions via shift current in two-dimensional inversion asymmetric insulators.

The precise determination of critical point is the basis to extract various critical properties of phase transitions. We identify that for two-dimensional inversion asymmetric insulators, with and without time-reversal symmetry, when topological phase transitions take place, all nonvanishing components of band-edge shift current tensor will reverse their signs in a singular way, regardless of what realistic value the temperature takes. This remarkable sign-reversal behavior of band-edge shift current tensor thus can be applied to determine the critical points of various topological phase transitions precisely, even for temperature-driven ones. We suggest concrete materials to test our predictions.
Study of Hindi Word Sense Disambiguation Based on Hindi WorldNet

In computational linguistics, word sense disambiguation (WSD) is an open problem of natural language processing, which governs the process of identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. In this paper, We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches with help of Hindi Wordnet prepared by IIT Bombay.
A New Vision For Artistic Segmentation

In this paper, we motivate the need for a new class of segmentation algorithms that partition images in ways that are artistically driven and aesthetically pleasing. Inspired by past work in computational parquetry, we present a novel algorithm to create a spatial feature-driven image segmentation that appeals to certain artistic forms and complements textural feature-based segmentation and matching. We hope that this contribution will motivate other researchers to explore how computer vision techniques can be leveraged to create art that transcends the digital into the physical.
Acta Polytechnica

Proportional Integral Derivative (PID) controllers are frequently used control methods for mechanical and electrical systems. Controller values are chosen either by calculation or by experimentation to obtain a satisfactory response in the system and to optimise the response. Sometimes the controller values do not quite capture the desired system response due to incorrect calculations or approximate entered values. In this case, it is necessary to add features that can make a comparison with the existing traditional system and add decision-making features to optimise the response of the system. In this article, the decision-making unit created for these control systems to provide a better control response and the PID system that contributes an extra control coefficient called ECCA-PID is presented. First, the structure and design of the traditional PID control system and the ECCA-PID control system are presented. After that, ECCA-PID and traditional PID methods’ step response of a quadratic system are examined. The results obtained show the effectiveness of the proposed control method.
Dynamic Rebalancing Optimization for Bike-sharing Systems: A Modeling Framework and Empirical Comparison

Bike-sharing systems have been implemented in multiple major cities, offering a low-cost and environmentally friendly transportation alternative to vehicles. Due to the stochastic nature of customer trips, stations are often unbalanced, resulting in unsatisfied demand. As a remedy, operators employ trucks to rebalance bikes among unbalanced stations. Given the complexity of the dynamic rebalancing planning, this topic has received significant attention from the Operations Research community. However, the planning problem requires significant simplifications such that optimization models remain computationally tractable. As a result, existing models have used a large variety of modeling assumptions and techniques regarding decision variables and constraints. Unfortunately, the impact of such assumptions on the solutions’ performance in practice remains generally unexplored. Indeed, existing simulation models to evaluate the performance of planning strategies also rely on simplifications, such as the aggregation of trips within the same time-period, therefore ignoring the original chronological sequence of trip demand. In this paper, we first systematically survey the literature on rebalancing problems and their modeling assumptions. We then propose a general modeling framework for multi-period dynamic rebalancing problems that can be easily adapted to different assumptions, including trip modeling, time discretization, trip distribution, and event sequences. We develop an instance generator to synthesize realistic station networks and customer trips, as well as a more realistic simulator to evaluate the operational performance of rebalancing strategies. Finally, extensive numerical experiments are carried out to analyze the effectiveness of various modeling assumptions and techniques. In this way, we identify the assumptions that empirically provide the most effective rebalancing strategies in practice. In particular, a set of specific trip distribution constraints as well as event sequences ignored in the previous literature seem to provide particularly good results.
90C22 Semidefinite programming 90C25 Convex programming 90C26 Nonconvex programming, global optimization 90C27 Combinatorial optimization 90C30 Nonlinear programming 58C05 Real-valued functions on manifolds 49M37 Numerical methods based on nonlinear programming

Semidefinite programming (SDP) with diagonal constraints arise in many optimization problems, such as Max-Cut, community detection and group synchronization. Although SDPs can be solved to arbitrary precision in polynomial time, generic convex solvers do not scale well with the dimension of the problem. In order to address this issue, Burer and Monteiro (Math Program 95(2):329-357, 2003) proposed to reduce the dimension of the problem by appealing to a low-rank factorization and solve the subsequent non-convex problem instead. In this paper, we present coordinate ascent based methods to solve this non-convex problem with provable convergence guarantees. More specifically, we prove that the block-coordinate maximization algorithm applied to the non-convex Burer-Monteiro method globally converges to a first-order stationary point with a sublinear rate without any assumptions on the problem. We further show that this algorithm converges linearly around a local maximum provided that the objective function exhibits quadratic decay. We establish that this condition generically holds when the rank of the factorization is sufficiently large. Furthermore, incorporating Lanczos method to the block-coordinate maximization, we propose an algorithm that is guaranteed to return a solution that provides 1 − O (1/r) approximation to the original SDP without any assumptions, where r is the rank of the factorization. This approximation ratio is known to be optimal (up to constants) under the unique games conjecture, and we can explicitly quantify the number of iterations to obtain such a solution.
Can cosmology detect hierarchical neutrino masses

We have carefully analyzed the potential of future cosmic microwave background (CMB) and large scale structure (LSS) measurements to probe neutrino masses. We perform a Fisher matrix analysis on a nine-dimensional cosmological parameter space and find that data from the Planck CMB experiment combined with the Sloan Digital Sky Survey (SDSS) can measure a value for the sum of all three active neutrino mass eigenstates of 0.12 eV at 95% C.L. This is almost at the level of the 0.06 eV mass suggested by current neutrino oscillation data. A future galaxy survey with an order of magnitude larger survey volume than the SDSS would allow for a neutrino mass determination of 0.03\char21{}0.05 eV (95% C.L.).
Role of Nanomaterials in the Fabrication of bioNEMS/MEMS for Biomedical Applications and towards Pioneering Food Waste Utilisation

bioNEMS/MEMS has emerged as an innovative technology for the miniaturisation of biomedical devices with high precision and rapid processing since its first R&D breakthrough in the 1980s. To date, several organic including food waste derived nanomaterials and inorganic nanomaterials (e.g., carbon nanotubes, graphene, silica, gold, and magnetic nanoparticles) have steered the development of high-throughput and sensitive bioNEMS/MEMS-based biosensors, actuator systems, drug delivery systems and implantable/wearable sensors with desirable biomedical properties. Turning food waste into valuable nanomaterials is potential groundbreaking research in this growing field of bioMEMS/NEMS. This review aspires to communicate recent progress in organic and inorganic nanomaterials based bioNEMS/MEMS for biomedical applications, comprehensively discussing nanomaterials criteria and their prospects as ideal tools for biomedical devices. We discuss clinical applications for diagnostic, monitoring, and therapeutic applications as well as the technological potential for cell manipulation (i.e., sorting, separation, and patterning technology). In addition, current in vitro and in vivo assessments of promising nanomaterials-based biomedical devices will be discussed in this review. Finally, this review also looked at the most recent state-of-the-art knowledge on Internet of Things (IoT) applications such as nanosensors, nanoantennas, nanoprocessors, and nanobattery.
Effect of 5-Aminolevulinic Acid Photodynamic Therapy with Transfer Factor Capsules in the Treatment of Multiple Plantar Warts

Background Plantar warts are a common cutaneous disease of the sole of the foot caused by human papillomavirus. Photodynamic therapy has gained increasing attention in the treatment of plantar warts. Objective To investigate the effect of photodynamic therapy combined with transfer factor capsules in the treatment of multiple plantar warts. Methods Sixty-one patients with multiple plantar warts who visited our outpatient department from September 2017 to August 2019 were randomly divided into two groups. Twenty-three patients received photodynamic therapy (treatment group) and thirty-eight received cryotherapy (control group). Both groups also received immune modulator transfer factor capsules. Skin lesion score, numeric rating scale- (NRS-) 10 score, recurrence rate, adverse reactions, and Dermatology Life Quality Index (DLQI) were analyzed in both groups. Results The mean skin lesion score improved from 13.39 ± 3.88 before treatment to 1.48 ± 2.50 after the last treatment in the treatment group and from 12.47 ± 2.99 before treatment to 4.47 ± 3.67 after the last treatment in the control group. The success rate after 3 months of treatment was 86.96% in the treatment group and 39.47% in the control group. After 3 months of follow-up, the recurrence rate was significantly lower in the treatment group (20%) than in the control group (53.33%). The mean DLQI score at three months after treatment was significantly lower in the treatment group (3.61 ± 1.16) than in the control group (6.31 ± 2.59). Conclusion Photodynamic therapy combined with immunomodulators significantly increased the cure rate and reduced the recurrence rate of multiple plantar warts compared with traditional cryotherapy combined with immunomodulators.
Rb-NMR study of the quasi-one-dimensional competing spin-chain compound R b 2 C u 2 M o 3 O 12

A Rb-NMR study has been performed on the quasi-one-dimensional competing spin chain $\mathrm{R}{\mathrm{b}}_{2}\mathrm{C}{\mathrm{u}}_{2}\mathrm{M}{\mathrm{o}}_{3}{\mathrm{O}}_{12}$ with ferromagnetic and antiferromagnetic exchange interactions on nearest-neighboring and next-nearest neighboring spins, respectively. The system changes from a gapped ground state at zero field to a gapless state at ${H}_{\mathrm{C}}\ensuremath{\simeq}2\phantom{\rule{0.16em}{0ex}}\mathrm{T}$, where the existence of magnetic order below 1 K was demonstrated by a broadening of the NMR spectrum, associated with a critical divergence of $1/{T}_{1}$. In the higher-temperature region, ${T}_{1}^{\ensuremath{-}1}$ showed a power-law-type temperature dependence, from which the field dependence of the Luttinger parameter $K$ was obtained and compared with theoretical calculations based on the spin nematic Tomonaga-Luttinger liquid (TLL) state.
An Infrared Census of DUST in Nearby Galaxies with Spitzer (DUSTiNGS). V. The Period–Luminosity Relation for Dusty Metal-poor AGB Stars

The survey for DUST in Nearby Galaxies with Spitzer (DUSTiNGS) has identified hundreds of candidate dust-producing asymptotic giant branch (AGB) stars in several nearby metal-poor galaxies. We have obtained multi-epoch follow-up observations for these candidates with the Spitzer Space Telescope and measured their infrared (IR) light curves. This has allowed us to confirm their AGB nature and investigate pulsation behavior at very low metallicity. We have obtained high-confidence pulsation periods for 88 sources in seven galaxies. We have confirmed DUSTiNGS variable star candidates with a 20% success rate and determined the pulsation properties of 19 sources already identified as thermally pulsing AGB stars. We find that the AGB pulsation properties are similar in all galaxies surveyed here, with no discernible difference between the DUSTiNGS galaxies (down to 1.4% solar metallicity; [Fe/H] = −1.85) and the far more metal-rich Magellanic Clouds (up to 50% solar metallicity; [Fe/H] = −0.38). These results strengthen the link between dust production and pulsation in AGB stars and establish the IR period–luminosity relation as a reliable tool (±4%) for determining distances to galaxies, regardless of metallicity.
Active Domain Adaptation for Fish Segmentation

Semantic segmentation is a promising approach for improving the sustainability and precision of deep sea ﬁshing practices, but there are challenges to scaling adoption. We study two of these challenges: few ground-truth labels and a wide variety of marine habitats and ﬁsh species to adapt to. We experiment with applying active learning and domain adaptation approaches, ﬁrst independently and then jointly, to handle these challenges.
Magnetic field - temperature phase diagram of quasi-two-dimensional organic superconductor lambda-(BETS)_2 GaCl_4 studied via thermal conductivity

The thermal conductivity kappa of the quasi-two-dimensional (Q2D) organic superconductor lambda-(BETS)_2 GaCl_4 was studied in the magnetic field H applied parallel to the Q2D plane. The phase diagram determined from this bulk measurement shows notable dependence on the sample quality. In dirty samples the upper critical field H_{c2} is consistent with the Pauli paramagnetic limiting, and a sharp change is observed in kappa(H) at H_{c2 parallel}. In contrast in clean samples H_{c2}(T) shows no saturation towards low temperatures and the feature in kappa(H) is replaced by two slope changes reminiscent of second-order transitions. The peculiarity was observed below ~ 0. 33T_c and disappeared on field inclination to the plane when the orbital suppression of superconductivity became dominant. This behavior is consistent with the formation of a superconducting state with spatially modulated order parameter in clean samples.