Miracle-dz/UniFAR-FTUs huggingface dataset:
Theory of Quantum Generative Learning Models with Maximum Mean Discrepancy

The intrinsic probabilistic nature of quantum mechanics invokes endeavors of designing quantum generative learning models (QGLMs) with computational advantages over classical ones. To date, two prototypical QGLMs are quantum circuit Born machines (QCBMs) and quantum generative adversarial networks (QGANs), which approximate the target distribution in explicit and implicit ways, respectively. Despite the empirical achievements, the fundamental theory of these models remains largely obscure. To narrow this knowledge gap, here we explore the learnability of QCBMs and QGANs from the perspective of generalization when their loss is speciﬁed to be the maximum mean discrepancy. Particularly, we ﬁrst analyze the generalization ability of QCBMs and identify their superiorities when the quantum devices can directly access the target distribution and the quantum kernels are employed. Next, we prove how the generalization error bound of QGANs depends on the employed Ansatz, the number of qudits, and input states. This bound can be further employed to seek potential quantum advantages in Hamiltonian learning tasks. Numerical results of QGLMs in approximating quantum states, Gaussian distribution, and ground states of parameterized Hamiltonians accord with the theoretical analysis. Our work opens the avenue for quantitatively understanding the power of quantum generative learning models.
Bayesian Reasoning and Evidence Communication

Many resources for forensic scholars and practitioners, such as journal articles, guidance documents, and textbooks, address how to make a value of evidence assessment in the form of a likelihood ratio ( LR ) when deciding between two competing propositions. These texts often describe experts presenting their LR values to other parties in the judicial system, such as lawyers, judges, and potentially jurors, but few texts explicitly address how a recipient is expected to utilize the provided LR value. Those that do often imply, or directly suggest, a hybrid modification of Bayes’ rule in which a decision maker multiplies their prior odds with another person’s assessment of LR to obtain their posterior odds. In this paper, we illustrate how someone adhering to Bayesian reasoning would update their personal uncertainty in response to someone else presenting a personal LR value (or any other form of an opinion) and emphasize that the hybrid approach is a departure from Bayesian reasoning. We further consider implications of recipients adhering to Bayesian reasoning on the role and ideal content of expert’s reports and testimony and address published responses to our 2017 paper (Lund and Iyer, 2017), where we previously argued that the hybrid equation is not supported by Bayesian reasoning.
OTFPF: Optimal Transport-Based Feature Pyramid Fusion Network for Brain Age Estimation with 3D Overlapped ConvNeXt

Chronological age of healthy brain is able to be predicted using deep neural networks from T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could serve as an effective biomarker for detecting aging-related diseases or disorders. In this paper, we propose an end-to-end neural network architecture, referred to as optimal transport based feature pyramid fusion (OTFPF) network, for the brain age estimation with T1 MRIs. The OTFPF consists of three types of modules: Optimal Transport based Feature Pyramid Fusion (OTFPF) module, 3D overlapped ConvNeXt (3D OL-ConvNeXt) module and fusion module. These modules strengthen the OTFPF network's understanding of each brain's semi-multimodal and multi-level feature pyramid information, and significantly improve its estimation performances. Comparing with recent state-of-the-art models, the proposed OTFPF converges faster and performs better. The experiments with 11,728 MRIs aged 3-97 years show that OTFPF network could provide accurate brain age estimation, yielding mean absolute error (MAE) of 2.097, Pearson's correlation coefficient (PCC) of 0.993 and Spearman's rank correlation coefficient (SRCC) of 0.989, between the estimated and chronological ages. Widespread quantitative experiments and ablation experiments demonstrate the superiority and rationality of OTFPF network. The codes and implement details will be released on GitHub: https://github.com/ZJU-Brain/OTFPF after final decision.
Optimal control for the Paneitz obstacle problem

In this paper, we study a natural optimal control problem associated to the Paneitz obstacle problem on closed 4-dimensional Riemannian manifolds. We show the existence of an optimal control which is an optimal state and induces also a conformal metric with prescribed Q-curvature. We show also C∞-regularity of optimal controls and some compactness results for the optimal controls. In the case of the 4-dimensional standard sphere, we characterize all optimal controls.
SoK: Rethinking Sensor Spoofing Attacks against Robotic Vehicles from a Systematic View

Robotic Vehicles (RVs) have gained great popularity over the past few years. Meanwhile, they are also demonstrated to be vulnerable to sensor spoofing attacks. Although a wealth of research works have presented various attacks, some key questions remain unanswered: are these existing works complete enough to cover all the sensor spoofing threats? If not, how many attacks are not explored, and how difficult is it to realize them? This paper answers the above questions by comprehensively systematizing the knowledge of sensor spoofing attacks against RVs. Our contributions are threefold. (1) We identify seven common attack paths in an RV system pipeline. We categorize and assess existing spoofing attacks from the perspectives of spoofer property, operation, victim characteristic and attack goal. Based on this systematization, we identify 4 interesting insights about spoofing attack designs. (2) We propose a novel action flow model to systematically describe robotic function executions and unexplored sensor spoofing threats. With this model, we successfully discover 103 spoofing attack vectors, 26 of which have been verified by prior works, while 77 attacks are never considered. (3) We design two novel attack methodologies to verify the feasibility of newly discovered spoofing attack vectors.
Fatores fisiológicos e antropométricos associados com a performance em subida no ciclismo off road Physiological and anthropometrical factors associated with uphill off-road cycling performance

The objectives of this study were: to analyze the reproducibility of the performance during a field test in uphill off-road cycling and to correlate physiological and anthropometrical factors with the performance in this modality. Ten trained cyclists (19.5 + 2.5 years, 62.8 + 8.7 kg, 173.5 + 6.8 cm, 24.5 + 19.0 months of training) performed, in different days, the following tests: three maximum uphill performances in the field; gradual continuous test for determination of the anaerobic threshold (AnT) and maximum aerobic power (Pmax); and Wingate test. The average values of performance of the 3 field tests (622 + 51.3; 614 + 50.1; 620.6 + 66.5 s) were not different and highly correlated (r = 0.84). The aerobic variables (Pmax and AnT) presented significant correlation with the best performance (P) only when expressed per unit of body mass (r = -0.73; r = -0.87, respectively). There was a significant correlation of P with 0% body fat and fatigue index obtained through the Wingate test (r = 0.72; r = 0.81, respectively). It can be concluded that the field test used to evaluate the performance in uphill off-road cycling is reliable, and that the main determinant factor of this performance is the AnT expressed per unit of body mass, indicating the importance of aerobic capacity and body composition on the selection and training of athletes of this sport.
Insight-HXMT Study of the Inner Accretion Disk in the Black Hole Candidate EXO 1846–031

We study the spectral evolution of the black hole candidate EXO 1846−031 during its 2019 outburst, in the 1–150 keV band, with the Hard X-ray Modulation Telescope. The continuum spectrum is well modeled with an absorbed disk-blackbody plus cutoff power law, in the hard, intermediate, and soft states. In addition, we detect an ≈6.6 keV Fe emission line in the hard intermediate state. Throughout the soft intermediate and soft states, the fitted inner disk radius remains almost constant; we suggest that it has settled at the innermost stable circular orbit (ISCO). However, in the hard and hard intermediate states, the apparent inner radius was unphysically small (smaller than the ISCO), even after accounting for the Compton scattering of some of the disk photons by the corona in the fit. We argue that this is the result of a high hardening factor, f col ≈ 2.0–2.7, in the early phases of the outburst evolution, well above the canonical value of 1.7 suitable for a steady disk. We suggest that the inner disk radius was already close to the ISCO in the low/hard state. Furthermore, we propose that this high value of the hardening factor in the relatively hard state was probably caused by the additional illuminating of the coronal irradiation onto the disk. Additionally, we estimate the spin parameter using the continuum-fitting method, over a range of plausible black hole masses and distances. We compare our results with the spin measured using the reflection-fitting method and find that the inconsistency of the two results is partly caused by different choices of f col.
Software tool-set for automated quantum system identification and device bring up

—We present a software tool-set which combines the theoretical, optimal control view of quantum devices with the practical operation and characterization tasks required for quan- tum computing. In the same framework, we perform model-based simulations to create control schemes, calibrate these controls in a closed-loop with the device (or in this demo - by emulating the experimental process) and ﬁnally improve the system model through minimization of the mismatch between simulation and experiment, resulting in a digital twin of the device. The model based simulator is implemented using TensorFlow, for numeric efﬁciency, scalability and to make use of automatic differenti- ation, which enables gradient-based optimization for arbitrary models and control schemes. Optimizations are carried out with a collection of state-of-the-art algorithms originated in the ﬁeld of machine learning. All of this comes with a user-friendly Qiskit interface, which allows end-users to easily simulate their quantum circuits on a high-ﬁdelity differentiable physics simulator.
The Geometric Theory of Phase Transitions

We develop a geometric theory of phase transitions (PTs) for Hamiltonian systems in the microcanonical ensemble. This theory allows to reformulate Bachmann's classification of PTs for finite-size systems in terms of geometric properties of the energy level sets (ELSs) associated to the Hamiltonian function. Specifically, by defining the microcanonical entropy as the logarithm of the ELS's volume equipped with a suitable metric tensor, we obtain an exact equivalence between thermodynamics and geometry. In fact, we show that any derivative of entropy with respect to the energy variable can be associated to a specific combination of geometric curvature structures of the ELSs which, in turn, are precise combinations of the potential function derivatives. In this way, we establish a direct connection between the microscopic description provided by the Hamiltonian and the collective behavior which emerges in a PT. Finally, we also analyze the behavior of the ELSs' geometry in the thermodynamic limit, showing that non-analyticities of the energy-derivatives of the entropy are caused by non-analyticities of certain geometric properties of the ELSs around the transition point. Finally, we validate the theory studying the PTs that occur in the $\phi^4$ and Ginzburg-Landau-like models.
Pembuatan Website Wisata Pulau Madura

Media for promotion is necessary to attract the attention of the public and tourists to come and visit island of Madura, Website is media that can be used to assist the promotion or publication with information that introduces attractions with easy access. This thesis will be made web-based application that utilizes MySQL, jQuery, JavaScript, YouTube iFrame API and the Google API with the programming language used is PHP. As well as making a video using Adobe Premiere Pro CS6 and Adobe After Effects Pro CS6 displayed on the page can be viewed by visitors.In this website, visitors can browse news, events, articles, gallery, destinations, and accommodation. Not only that, visitors can searching for destination through a search bar and a map using Google Map API and use rating and review on destinations. Visitors can also make requests to add destinations, news, events, articles, and accommodation. The test results indicate that the website created using MySQL, jQuery, JavaScript, YouTube iFrame API and the Google Map API can run well in Chrome, Firefox, and Safari browser. Geolocation function with Google Map API that used for map direction and nearest location cannot be used effectively when user use Chrome version 50. The results of questionnaires that obtained from 12 respondents concluded the percentage of overall application, design, navigation, and facilities provided on website with the percentage 25% for 5 points, 58.3% for 4 points, and 16.7% for 3 points with maximum 5 points.
Balancing Connected Colourings of Graphs

We show that the edges of any graph $G$ containing two edge-disjoint spanning trees can be blue/red coloured so that the blue and red graphs are connected and the blue and red degrees at each vertex differ by at most four. This improves a result of Hörsch. We discuss variations of the question for digraphs, infinite graphs and a computational question, and resolve two further questions of Hörsch in the negative.
Notes on Spinors and Polyforms I: General Case

It is well-known that the Cliﬀord algebra Cl(2 n ) can be given a description in terms of creation/annihilation operators acting in the space of inhomogeneous diﬀerential forms on C n . We found it convenient to refer to such inhomogeneous diﬀerential forms as polyforms. Geometrically, the construction proceeds by choosing a complex structure J on R 2 n . Spinors are then polyforms on one of the two totally-isotropic subspaces C n that arise as eigenspaces of J . There is a similar and also well-known description in the split signature case Cl( n, n ), with diﬀerential forms now being those on R n . In this case the model is constructed by choosing a paracomplex structure I on R n,n , and spinors are polyforms on one of the totally null eigenspaces R n of I . The main purpose of the paper is to describe the geometry of an analogous construction in the case of a general Cliﬀord algebra Cl( r,s ) , r + s = 2 m . We show that in general a creation/annihilation operator model is in correspondence with a new type of geometric structure on R r,s , which provides a splitting R r,s = R 2 k, 2 l ⊕ R n,n and endows the ﬁrst factor with a complex structure and the second factor with a paracomplex structure. We refer to such geometric structure as a mixed structure. It can be described as a complex linear combination K = I + i J of a paracomplex and a complex structure such that K 2 = I and K ¯ K is a product structure. In turn, the mixed structure is in correspondence with a pair of pure spinors whose null subspaces are the eigenspaces of K . The conclusion is then that there is in general not one, but several possible creation/annihilation operator models for a given Cliﬀord algebra. The number of models is the number of diﬀerent types of pure spinors (distinguished by the real index, see the main text) that exists in a given signature. To illustrate this geometry, we explicitly describe all the arising models for Cl( r, s ) with r ≥ s, r + s = 2 m ≤ 6.
Reconfigurable Robots for Scaling Reef Restoration

Coral reefs are under increasing threat from the impacts of climate change. Whilst current restoration approaches are effective, they require significant human involvement and equipment, and have limited deployment scale. Harvesting wild coral spawn from mass spawning events, rearing them to the larval stage and releasing the larvae onto degraded reefs is an emerging solution for reef restoration known as coral reseeding. This paper presents a reconfigurable autonomous surface vehicle system that can eliminate risky diving, cover greater areas with coral larvae, has a sensory suite for additional data measurement, and requires minimal non-technical expert training. A key feature is an on-board real-time benthic substrate classification model that predicts when to release larvae to increase settlement rate and ultimately, survivability. The presented robot design is reconfigurable, light weight, scalable, and easy to transport. Results from restoration deployments at Lizard Island demonstrate improved coral larvae release onto appropriate coral substrate, while also achieving 21.8 times more area coverage compared to manual methods.
Upper Bounds to Genome Rearrangement Problem using Prefix Transpositions

A Genome rearrangement problem studies large-scale mutations on a set of DNAs in living organisms. Various rearrangements like reversals, transpositions, translocations, fissions, fusions, and combinations and different variations have been studied extensively by computational biologists and computer scientists over the past four decades. From a mathematical point of view, a genome is represented by a permutation. The genome rearrangement problem is interpreted as a problem that transforms one permutation into another in a minimum number of moves under certain constraints depending on the chosen rearrangements. Finding the minimum number of moves is equivalent to sorting the permutation with the given rearrangement. A transposition is an operation on a permutation that moves a sublist of a permutation to a different position in the same permutation. A \emph{Prefix Transposition}, as the name suggests, is a transposition that moves a sublist which is a prefix of the permutation. In this thesis, we study prefix transpositions on permutations and present a better upper bound for sorting permutations with prefix transpositions. A greedy algorithm called the \emph{generalised sequence length algorithm} is defined as an extension of the sequence length algorithm where suitable alternate moves are also considered. This algorithm is used to sequentially improve the upper bound to $n-\log_{3.3} n$ and $n-\log_3 n$. In the latter part of the thesis, we defined the concept of a \emph{block}. We used it along with the greedy moves of the generalised sequence length algorithm to get an upper bound of $n-\log_2 n$ to sort permutations by prefix transpositions.
Novel Basic Block of Multilevel Inverter Using Reduced Number of On-State Switches and Cascaded Circuit Topology

In this paper a basic block of novel topology of multilevel inverter is proposed. The proposed approach significantly requires reduced number of dc voltage sources and power switches to attain maximum number of output voltage levels. By connecting basic blocks in series a cascaded multilevel topology is developed. Each block itself is also a multilevel inverter. Analysis of proposed topology is carried out in symmetric as well as asymmetric operating modes. The topology is investigated through computer simulation using MATLAB/Simulink and validated experimentally on prototype in the laboratory.
Characterizing the country-wide adoption and evolution of the Jodel messaging app in Saudi Arabia

Social media is subject to constant growth and evolution, yet little is known about their early phases of adoption. To shed light on this aspect, this paper empirically characterizes the initial and country-wide adoption of a new type of social media in Saudi Arabia that happened in 2017. Unlike established social media, the studied network Jodel is anonymous and location-based to form hundreds of independent communities country-wide whose adoption pattern we compare. We take a detailed and full view from the operators perspective on the temporal and geographical dimension on the evolution of these different communities -- from their very first the first months of establishment to saturation. This way, we make the early adoption of a new type of social media visible, a process that is often invisible due to the lack of data covering the first days of a new network.
Gradient-Free optimization algorithm for single-qubit quantum classifier

In the paper, a gradient-free optimization algorithm for single-qubit quantum classifier is proposed to overcome the effects of barren plateau caused by quantum devices. A rotation gate RX({\phi}) is applied on a single-qubit binary quantum classifier, and the training data and parameters are loaded into {\phi} with the form of vector-multiplication. The cost function is decreased by finding the value of each parameter that yield the minimum expectation value of measuring the quantum circuit. The algorithm is performed iteratively for all parameters one by one, until the cost function satisfies the stop condition. The proposed algorithm is demonstrated for a classification task and is compared with that using Adam optimizer. Furthermore, the performance of the single-qubit quantum classifier with the proposed gradient-free optimization algorithm is discussed when the rotation gate in quantum device is under different noise. The simulation results show that the single-qubit quantum classifier with proposed gradient-free optimization algorithm can reach a high accuracy faster than that using Adam optimizer. Moreover, the proposed gradient-free optimization algorithm can quickly completes the training process of the single-qubit classifier. Additionally, the single-qubit quantum classifier with proposed gradient-free optimization algorithm has a good performance in noisy environments.
Scaling-up Generalized Planning as Heuristic Search with Landmarks

Landmarks are one of the most effective search heuristics for classical planning, but largely ignored in generalized planning. Generalized planning (GP) is usually addressed as a combinatorial search in a given space of algorithmic solutions, where candidate solutions are evaluated w.r. t. the instances they solve. This type of solution evaluation ignores any sub-goal information that is not explicit in the representation of the planning instances, causing plateaus in the space of candidate generalized plans. Furthermore, node expansion in GP is a run-time bottleneck since it requires evaluating every child node over the entire batch of classical planning instances in a GP problem. In this paper we define a landmark counting heuristic for GP (that considers sub-goal information that is not explicitly represented in the planning instances), and a novel heuristic search algorithm for GP (that we call PGP) and that progressively processes subsets of the planning instances of a GP problem. Our two orthogonal contributions are analyzed in an ablation study, showing that both improve the state-of-the-art in GP as heuristic search, and that both benefit from each other when used in combination.