Miracle-dz/UniFAR-FTUs huggingface dataset:
A NOTE ON CONTACT STRUCTURES

We construct two contact structures on a homology sphere M , that are homotopic through 2-plane fields, but are not isotopic as contact structures. A diffeomorphism of M permutes these two contact structures. In [LM] Lisca and Matic gave examples of homotopic but not isotopic contact structures. In this note we give a simple construction of another such example. Unlike the examples of Lisca and Matic, in our example the group of diffeomorphism of the 3-manifold acts nontrivially on the set of path components of oriented contact structures of the manifold, while the action of this group is trivial on the set of path components of the oriented tangent plane distributions. Our construction of contact structures uses theorem of Y. Eliashberg, characterizing symplectic 4-manifolds with pseudo-convex boundary (PC -manifolds). Theorem 1 ([E]) : Let X = B ∪ (1− handles) ∪ (2− handles) be fourdimensional handlebody with one 0-handle and no 3or 4-handles. Then: • The standard PC structure on B can be extended over 1-handles so that manifold X1 = B 4 ∪ (1− handles) has pseudo-convex boundary. • If each 2-handle is attached to ∂X1 along a Legendrian knot with framing one less then Thurston-Bennequin framing of this knot, then the symplectic form on X1 can be extended over 2-handles to a symplectic form on X, which makes X a PC manifold. We can visualize pseudo-convex handlebodies as follows: Take a 0-handle to be the unit ball B in C with the induced symplectic structure; choose coordinates in R ⊂ S = ∂B, so that the induced contact structure ξ0 on R is the kernel of the form λ0 = dz+ xdy. We also assume that the centers of the attaching balls of each 1-handle lies on the plane {x = constant}. Projection of a Legendrian link on the plane {x = 0} has intersection only of the type shown on Figure 1 (coming from left handed crossing), no vertical tangencies and all minima and maxima in y-direction are cusps. Moreover, every projection with these properties is a projection of some Legendrian link. Thurston-Bennequin invariant of a Legendrian knot α can be calculated by: tb(α) = bb(α)− (number of right cusps) where bb(α) is the blackboard (yz-plane) framing of the projection of α. Any PC-manifoldX induces a contact structure on the boundary 3-manifold Y = ∂X by restricting the dual K∗ of the canonical line bundleK → X. Furthermore if α
A Simplified Approach to Approximate Diffusion Processes Widely Used in Finance

We propose a simplified approach to approximate a variety of heteroskedastic diffusions widely used in finance to describe the evolution of state variables such as equity prices, short interest rates, and others. In contrast to the common approach based on approximating a new homoskedastic process obtained by transforming the original heteroskedastic one, we build up binomial and trinomial trees that directly discretize the initial process. Despite this, the proposed approximation models are based on recombining lattices that converge weakly to the corresponding limiting diffusion. Numerical results show that the proposed algorithms are efficient and that they compute accurate prices.
Orbit Modulation Method Based on Mean Orbit Elements

An orbital modulation method by controlling the corresponding transient orbit errors of mean orbit control targets was proposed. On the basis of analytical orbit theory, the state transition matrix from mean to transient orbit errors was put forward. A proper control strategy controlling the transient orbit element errors to realize the modulation of mean orbit element errors was given. Simulation results show that the mean orbit element errors can be modulated to meet the given error range within one period by the method proposed in this paper, and it is brief in computational formula and suitable for autonomous calculation and laying the theoretical foundation for the modulation of autonomous orbit in the satellite.
The Complexity of Diagonalization

We survey recent progress on efficient algorithms for approximately diagonalizing a square complex matrix in the models of rational (variable precision) and finite (floating point) arithmetic. This question has been studied across several research communities for decades, but many mysteries remain. We present several open problems which we hope will be of broad interest.
An atmospheric electrical voltmeter follower

Horizontal passive antennas used to sense the potential of the atmosphere above the earth’s surface demand high performance from attached electrometer voltmeter circuits. The floating follower circuit described here allows precision dc measurements of potential difference in the range ±10 V, while maintaining input currents of order 10−15 A. Voltage offsets over most of the dynamic range are less than 50 μV, allowing precise guarding of the input electrode to further minimize input leakage currents. The battery‐operated system is well suited to atmospheric electrical measurements using horizontal antennas operating within 10 cm of the earth’s surface, and provides an inexpensive means of precision high impedance voltage measurements.
Taxonomy Completion with Probabilistic Scorer via Box Embedding

Taxonomy completion, a task aimed at automatically enriching an existing taxonomy with new concepts, has gained significant interest in recent years. Previous works have introduced complex modules, external information, and pseudo-leaves to enrich the representation and unify the matching process of attachment and insertion. While they have achieved good performance, these introductions may have brought noise and unfairness during training and scoring. In this paper, we present TaxBox, a novel framework for taxonomy completion that maps taxonomy concepts to box embeddings and employs two probabilistic scorers for concept attachment and insertion, avoiding the need for pseudo-leaves. Specifically, TaxBox consists of three components: (1) a graph aggregation module to leverage the structural information of the taxonomy and two lightweight decoders that map features to box embedding and capture complex relationships between concepts; (2) two probabilistic scorers that correspond to attachment and insertion operations and ensure the avoidance of pseudo-leaves; and (3) three learning objectives that assist the model in mapping concepts more granularly onto the box embedding space. Experimental results on four real-world datasets suggest that TaxBox outperforms baseline methods by a considerable margin and surpasses previous state-of-art methods to a certain extent.
3D Registration with Maximal Cliques

As a fundamental problem in computer vision, 3D point cloud registration (PCR) aims to seek the optimal pose to align a point cloud pair. In this paper, we present a 3D registration method with maximal cliques (MAC). The key insight is to loosen the previous maximum clique constraint, and mine more local consensus information in a graph for accurate pose hypotheses generation: 1) A compatibility graph is constructed to render the affinity relationship between initial correspondences. 2) We search for maximal cliques in the graph, each of which represents a consensus set. We perform node-guided clique selection then, where each node corresponds to the maximal clique with the greatest graph weight. 3) Transformation hypotheses are computed for the selected cliques by the SVD algorithm and the best hypothesis is used to perform registration. Extensive experiments on U3M, 3DMatch, 3DLoMatch and KITTI demonstrate that MAC effectively increases registration accuracy, outperforms various state-of-the-art methods and boosts the performance of deep-learned methods. MAC combined with deep-learned methods achieves state-of-the-art registration recall of 95.7% /78.9% on 3DMatch /3DLoMatch.
TORINO Repository ISTITUZIONALE

Vitamin-V is a 2023-2025 Horizon Europe project that aims to develop a complete RISC-V open-source software stack for cloud services with comparable performance to the cloud-dominant x86 counterpart and a powerful virtual execution environment for software development, validation, verification, and test that considers the relevant RISC-V ISA extensions for cloud deployment
Generalized K\"ahler manifolds via mapping tori

Starting from the product of a $3$-torus and a compact K\"ahler (respectively, hyperK\"ahler) manifold we construct via mapping tori generalized K\"ahler manifolds of split (respectively, non-split) type. In this way we obtain new non-K\"ahler examples and we recover the known examples of generalized K\"ahler solvmanifolds. Moreover, we investigate the formality and the Dolbeault cohomology of the generalized K\"ahler mapping tori.
Bioactive peptides for anticancer therapies

ABSTRACT Cancer is a serious concern in public health worldwide. Numerous modalities including surgery, radiotherapy, and chemotherapy, have been used for cancer therapies in clinic. Despite progress in anticancer therapies, the usage of these methods for cancer treatment is often related to deleterious side effects and multidrug resistance of conventional anticancer drugs, which have prompted the development of novel therapeutic methods. Anticancer peptides (ACPs), derived from naturally occurring and modified peptides, have received great attention in these years and emerge as novel therapeutic and diagnostic candidates for cancer therapies, because of several advantages over the current treatment modalities. In this review, the classification and properties of ACPs, the mode of action and mechanism of membrane disruption, as well as the natural sources of bioactive peptides with anticancer activities were summarised. Because of their high efficacy for inducing cancer cell death, certain ACPs have been developed to work as drugs and vaccines, evaluated in varied phases of clinical trials. We expect that this summary could facilitate the understanding and design of ACPs with increased specificity and toxicity towards malignant cells and with reduced side effects to normal cells.
Breakthrough treatments for accelerated wound healing

Skin injuries across the body continue to disrupt everyday life for millions of patients and result in prolonged hospital stays, infection, and death. Advances in wound healing devices have improved clinical practice but have mainly focused on treating macroscale healing versus underlying microscale pathophysiology. Consensus is lacking on optimal treatment strategies using a spectrum of wound healing products, which has motivated the design of new therapies. We summarize advances in the development of novel drug, biologic products, and biomaterial therapies for wound healing for marketed therapies and those in clinical trials. We also share perspectives for successful and accelerated translation of novel integrated therapies for wound healing.
Mechanically conditioned cell sheets cultured on thermo-responsive surfaces promote bone regeneration

ABSTRACT Cell sheet-based scaffold-free technology holds promise for tissue engineering applications and has been extensively explored during the past decades. However, efficient harvest and handling of cell sheets remain challenging, including insufficient extracellular matrix content and poor mechanical strength. Mechanical loading has been widely used to enhance extracellular matrix production in a variety of cell types. However, currently, there are no effective ways to apply mechanical loading to cell sheets. In this study, we prepared thermo-responsive elastomer substrates by grafting poly(N-isopropyl acrylamide) (PNIPAAm) to poly(dimethylsiloxane) (PDMS) surfaces. The effect of PNIPAAm grafting yields on cell behaviours was investigated to optimize surfaces suitable for cell sheet culturing and harvesting. Subsequently, MC3T3-E1 cells were cultured on the PDMS-g-PNIPAAm substrates under mechanical stimulation by cyclically stretching the substrates. Upon maturation, the cell sheets were harvested by lowering the temperature. We found that the extracellular matrix content and thickness of cell sheet were markedly elevated upon appropriate mechanical conditioning. Reverse transcription quantitative polymerase chain reaction and Western blot analyses further confirmed that the expression of osteogenic-specific genes and major matrix components were up-regulated. After implantation into the critical-sized calvarial defects of mice, the mechanically conditioned cell sheets significantly promoted new bone formation. Findings from this study reveal that thermo-responsive elastomer, together with mechanical conditioning, can potentially be applied to prepare high-quality cell sheets for bone tissue engineering.
Prediction of concrete strength using response surface function modified depth neural network

In order to overcome the discreteness of input data and training data in deep neural network (DNN), the multivariable response surface function was used to revise input data and training data in this paper. The loss function based on the data on the response surface was derived, DNN based on multivariable response surface function (MRSF-DNN) was established. MRSF-DNN model of recycled brick aggregate concrete compressive strength was established, in which coarse aggregate volume content, fine aggregate volume content and water cement ratio are influencing factors. Furthermore, the predictive analysis and extended analysis of MRSF-DNN model were carried out. The results show that: MRSF-DNN model had high prediction accuracy, the correlation coefficient between the real values and the forecast values was 0.9882, the relative error was between -0.5% and 1%. Furthermore, MRSF-DNN had more stable prediction ability and stronger generalization ability than DNN.
Research on yokeless double-sided multi-tooth flux-switching linear motor

Purpose – Due to the advantages of direct driven, high thrust density, and high efficiency, flux-switching linear motor (FSLM) is required for many applications, including aerospace and automotive. However, the vibration caused by detent force and difficulties in the assembly produced by the large normal force become the barriers that restrict its development. The paper aims to discuss these issues. Design/methodology/approach – In order to improve the electromagnetic performance of double-sided multi-tooth FSLM (DMTFSLM), a yokeless DMTFSLM with moving primary is proposed and compared with normal DMTFSLM. Moreover, with theoretical analysis, the selection principle of slot-pole number combination is obtained. DMTFSLMs with four slot/pole combinations, 6s/16p, 6s/17p, 6s/19p, 6s/20p, are analyzed based on finite element analysis model. Finally, several parameters of this yokeless DMTFSLM have been optimized to obtain the better performance. Findings – In yokeless DMTFSLM, it is found that the asymmetry of.
Multidirectional Associative Memory Neural Network Circuit Based on Memristor

Multidirectional associative memory neural network(MAMNN) is a direct extension of bidirectional associative memory neural network, which can handle multiple associations. In this work, a circuit of MAMNN based on memristor is proposed, which simulates the complex associative memory behavior more in line with the brain mechanism. Firstly, the basic associative memory circuit is designed, which is mainly composed of memristive weight matrix circuit, adder module and activation circuit. It realizes the associative memory function of single-layer neurons input and single-layer neurons output, so that the information can be transmitted unidirectionally between double-layer neurons. Secondly, on this basis, an associative memory circuit with multi-layer neurons input and single-layer neurons output is realized, which makes information transfer unidirectionally between multi-layer neurons. Finally, several identical circuit architectures are extended, and they are combined into a MAMNN circuit through the feedback connection from the output to the input, which realizes the bidirectional transmission of information between multi-layer neurons. Pspice simulation shows that: 1) When single-layer neurons are selected to input data, the circuit can associate data from other multi-layer neurons, realizing one-to-many associative memory function in the brain. 2) When multi-layer neurons are selected to input data, the circuit can associate the target data and realize the many-to-one associative memory function in the brain. The MAMNN circuit is applied to the field of image processing, which can associate and restore damaged binary images, showing strong robustness.
A new type of intermittency from a ring of four coupled phase-locked loops

This paper investigates a new type of intermittency from a ring of four coupled phase-locked loops (PLL's). This system can be represented by a six-dimensional nonlinear autonomous differential equation that has a four-dimensional invariant manifold named H. With a quasi-attractive property, this invariant manifold causes a type of intermittency. Namely, long laminar phases in H and short bursts out of H alternate irregularly. Different from the well-known on-off intermittency, the core of this intermittency is not a chaotic set in H, but two kinds of semistable periodic orbits in H called the entrance set and the exit set. We try to clarify the mechanism of this intermittency by using bifurcation analysis of these periodic orbits.
Continuum Deductions from Molecular Hydrodynamics

Since a fluid is composed of molecules, one always has the option of calculating its static or dynamic properties by computing the motion of these constituents. For most purposes such a procedure is very inefficient, because it provides detailed information at molecular length scales, which are far beneath the usual realm of interest for continuum fluid mechanics. There are, however, situations where the microscopic details of a fluid flow are interesting if not crucial. For example, fluids in microscopic geometries or under high stress may exhibit deviations from the continuum equations, and one may wish to calculate such effects from first principles. Alternatively, in some problems the boundary conditions to be applied to the Navier-Stokes equations are not fully established or are unsatisfactory, as in the presence of moving contact lines or at the edge of a porous
NOTES AND CORRESPONDENCE Ensemble Square Root Filters

Ensemble data assimilation methods assimilate observations using state-space estimation methods and lowrank representations of forecast and analysis error covariances. A key element of such methods is the transformation of the forecast ensemble into an analysis ensemble with appropriate statistics. This transformation may be performed stochastically by treating observations as random variables, or deterministically by requiring that the updated analysis perturbations satisfy the Kalman filter analysis error covariance equation. Deterministic analysis ensemble updates are implementations of Kalman square root filters. The nonuniqueness of the deterministic transformation used in square root Kalman filters provides a framework to compare three recently proposed ensemble data assimilation methods.
Impact of hepatitis C cure on risk of mortality and morbidity in people with HIV after antiretroviral therapy initiation

Objective: Hepatitis C virus (HCV) co-infection is associated with increased morbidity and mortality in people with HIV (PWH). Sustained virological response (SVR) decreases the risk of HCV-associated morbidity. We compared mortality, risk of AIDS-defining events, and non-AIDS nonliver (NANL) cancers between HCV-co-infected PWH who reached SVR and mono-infected PWH. Design: Adult PWH from 21 cohorts in Europe and North America that collected HCV treatment data were eligible if they were HCV-free at the time of ART initiation. Methods: Up to 10 mono-infected PWH were matched (on age, sex, date of ART start, HIV acquisition route, and being followed at the time of SVR) to each HCV-co-infected PWH who reached SVR. Cox models were used to estimate relative hazards (hazard ratio) of all-cause mortality, AIDS-defining events, and NANL cancers after adjustment. Results: Among 62 495 PWH, 2756 acquired HCV, of whom 649 reached SVR. For 582 of these, at least one mono-infected PWH could be matched, producing a total of 5062 mono-infected PWH. The estimated hazard ratios comparing HCV-co-infected PWH who reached SVR with mono-infected PWH were 0.29 [95% confidence interval (CI) 0.12–0.73] for mortality, 0.85 [0.42–1.74] for AIDS-defining events, and 1.21 [0.86–1.72] for NANL cancer. Conclusion: PWH who reached SVR a short time after HCV acquisition were not at higher risk of overall mortality compared with mono-infected PWH. However, the apparent higher risk of NANL cancers in HCV-co-infected PWH who reached SVR after a DAA-based treatment compared with mono-infected PWH, though compatible with a null association, suggests a need for monitoring of those events following SVR.
An improved algorithm for the detection of vehicle group targets in high-resolution SAR images

In this paper, the detection of vehicle group targets in high-resolution SAR images has been investigated. Theoretical analysis has been carried out by statistical methods and the formulas of threshold and parameter estimations of three detection algorithms are obtained. The results show that global parameter estimation is of good effect and there are more false alarms in conventional two-parameter CFAR and single look standard CFAR detection algorithms. We present an improved multi-look de-speckling CFAR detection algorithm, which shows exact target detection, little false alarm and clear target details. The parameter selection and optimal parameters are also given.
Several serum lipid metabolites are associated with relapse risk in pediatric-onset multiple sclerosis

Background: The circulating metabolome is altered in multiple sclerosis (MS), but its prognostic capabilities have not been extensively explored. Lipid metabolites might be of particular interest due to their multiple roles in the brain, as they can serve as structural components, energy sources, and bioactive molecules. Gaining a deeper understanding of the disease may be possible by examining the lipid metabolism in the periphery, which serves as the primary source of lipids for the brain. Objective: To determine if altered serum lipid metabolites are associated with the risk of relapse and disability in children with MS. Methods: We collected serum samples from 61 participants with pediatric-onset MS within 4 years of disease onset. Prospective longitudinal relapse data and cross-sectional disability measures (Expanded Disability Status Scale [EDSS]) were collected. Serum metabolomics was performed using untargeted liquid chromatography and mass spectrometry. Individual lipid metabolites were clustered into pre-defined pathways. The associations between clusters of metabolites and relapse rate and EDSS score were estimated utilizing negative binomial and linear regression models, respectively. Results: We found that serum acylcarnitines (relapse rate: normalized enrichment score [NES] = 2.1, q = 1.03E–04; EDSS: NES = 1.7, q = 0.02) and poly-unsaturated fatty acids (relapse rate: NES = 1.6, q = 0.047; EDSS: NES = 1.9, q = 0.005) were associated with higher relapse rates and EDSS, while serum phosphatidylethanolamines (relapse rate: NES = −2.3, q = 0.002; EDSS: NES = −2.1, q = 0.004), plasmalogens (relapse rate: NES = −2.5, q = 5.81E–04; EDSS: NES = −2.1, q = 0.004), and primary bile acid metabolites (relapse rate: NES = −2.0, q = 0.02; EDSS: NES = −1.9, q = 0.02) were associated with lower relapse rates and lower EDSS. Conclusion: This study supports the role of some lipid metabolites in pediatric MS relapses and disability.
New Clues to Cardiovascular Disease: Erythrocyte Lifespan

Determination of erythrocyte lifespan is an important part of the diagnosis of hemolytic diseases. Recent studies have revealed alterations in erythrocyte lifespan among patients with various cardiovascular diseases, including atherosclerotic coronary heart disease, hypertension, and heart failure. This review summarizes the progress of research on erythrocyte lifespan in cardiovascular diseases.