Miracle-dz/UniFAR-FTUs huggingface dataset:
RXs Directions based Codebook Solution for Passive RIS Beamforming

Recently, reconfigurable intelligent surface (RIS) has gained popularity to overcome blockage issues and boost coverage in advanced 6G networks. Passive beamforming (PBF) process redirects incident signals from the transmitter (TX) toward the receiver (RX) by adjusting the amplitudes and phase shifts of RIS elements. Though channel estimation (CE)-based PBF schemes are optimal, they need high overheads and time consumption, especially with a substantial number of RIS elements. In contrast, codebook (CB) based PBF solutions explore limited reflection patterns (RPs) to determine the optimal one using a predefined metric, resulting in sub-optimal performance. However, these still require high power and time due to the size of the used CB. To resolve these issues, we suggest a direction-based PBF (D-PBF) scheme, aiming to map the RX's directions to the codebook RPs. Then, this information is stored in an updated database (DB), and if a matching happens between an incoming RX and a specific RP exists in the DB, the proposed scheme directly selects this RP to configure the RIS elements. If not, the scheme records this codeword for future searches. In the event of a failed match, the D-PBF scheme searches through all the recorded RPs to select the optimal one and updates the DB accordingly. After a period, that depends on the CB size, the DB converges, eliminating the need of searching for the optimal RP. The proposed scheme significantly reduces overhead, power, and time requirements compared to the CE and conventional CB-based solutions, while maintaining satisfactory performance in terms of effective rate. For example, it can obtain at least 80% of optimal effective rate with 103 lower computational complexity comparable to lowest complexity CE based scheme.
Vorticity and level-set variations of invariant current bound steady-state dissipation

A non-vanishing entropy production rate is a hallmark of non-equilibrium stationary states and is therefore at the heart of non-equilibrium thermodynamics. It is a manifestation of a steady circulation $J_{\rm inv}$ along the level sets of the invariant density $\rho_{\rm inv}$, and is thus generically used to quantify how far a steady system is driven out of equilibrium. While it is well known that there exists a continuum of distinct steady states with the same invariant measure, the question how the geometry and topology of the invariant current a priori affect dissipation remained elusive. For confined irreversible diffusions we identify two minimal descriptors, the $\rho_{\rm inv}$-weighted vorticity and the variation of $J_{\rm inv}$ along level sets of $\rho_{\rm inv}$, and prove that these jointly bound from above the steady-state entropy production rate. In regions where $\rho_{\rm inv}$ is close to Gaussian the bound is dominated solely by the vorticity of the drift field and in the low-noise (Freidlin-Wentzel) limit by any non-potential contribution to the drift, rendering $J_{\rm inv}$ virtually constant along the level sets of $\rho_{\rm inv}$.
Schwarzschild deformed supergravity background: possible geometry origin of fermion generations and mass hierarchy

TThe problem of fermion masses hierarchy in the Standard Model is considered on a toy model of a 10-dimensional space-time with a IIA supergravity type background. Dirac equation on this background, after compactification of extra 4- and 1-dimensional subspaces, gives the spectrum of Fermi fields which profiles in 5 dimensions and corresponding Higgs generated masses in 4 dimensions depend on the eigenvalues of Dirac operator on the named compact subspaces. Schwarzschild Euclidean deformation of the supergravity throat with the"apple-shaped"conical singularity permits to leave only three non-divergent angular modes interpreted as three generations of the down-type quarks. Calculated ratio $m_{d} / m_{s} = e^{-3}$ exactly coincides with its experimentally observed value for integer values of two free parameters of the 10-dimensional background. Equations for non-chiral modes coincide with the non-relativistic Schr\"odinger equation for an electron moving in a Coulomb field; the corresponding small fermion masses generated by the twisted boundary conditions are expressed through the degenerate hypergeometric functions.
Nonsmooth Control Barrier Functions for Obstacle Avoidance between Convex Regions

In this paper, we focus on non-conservative obstacle avoidance between robots with control affine dynamics with strictly convex and polytopic shapes. The core challenge for this obstacle avoidance problem is that the minimum distance between strictly convex regions or polytopes is generally implicit and non-smooth, such that distance constraints cannot be enforced directly in the optimization problem. To handle this challenge, we employ non-smooth control barrier functions to reformulate the avoidance problem in the dual space, with the positivity of the minimum distance between robots equivalently expressed using a quadratic program. Our approach is proven to guarantee system safety. We theoretically analyze the smoothness properties of the minimum distance quadratic program and its KKT conditions. We validate our approach by demonstrating computationally-efficient obstacle avoidance for multi-agent robotic systems with strictly convex and polytopic shapes. To our best knowledge, this is the first time a real-time QP problem can be formulated for general non-conservative avoidance between strictly convex shapes and polytopes.
Prediction of Annual Snow Accumulation Using a Recurrent Graph Convolutional Approach

The precise tracking and prediction of polar ice layers can unveil historic trends in snow accumulation. In recent years, airborne radar sensors, such as the Snow Radar, have been shown to be able to measure these internal ice layers over large areas with a fine vertical resolution. In our previous work, we found that temporal graph convolutional networks perform reasonably well in predicting future snow accumulation when given temporal graphs containing deep ice layer thickness. In this work, we experiment with a graph attention network-based model and used it to predict more annual snow accumulation data points with fewer input data points on a larger dataset. We found that these large changes only very slightly negatively impacted performance.
High-resolution acoustic field mapping of gigahertz phononic crystals with atomic force microscopy

On-chip technology based on acoustic waves is a strong asset in modern telecommunication with the prospects of becoming a cornerstone of next-generation devices. In this context, mapping and manipulating acoustic waves through coherent scattering is pivotal for a non-trivial control of the flow of acoustic energy, which could consequently enable advanced information manipulation. To this end, here a technique for mapping acoustic fields is introduced and used for characterizing $\mu$m-sized phononic crystals defined in GaAs slabs and excited by GHz surface acoustic waves (SAWs) based on atomic force microscopy. It is shown that incoherent scattering excites a wide distribution of modes, which enables the mapping of the dispersion relation of the two-dimensional structures, while the phononic crystal symmetry directly correlates with coherent scattering effects. Enabling the use of acoustic atomic force microscopy and understanding the role of scattering are of paramount importance for the versatile use of GHz acoustic waves in technological applications, setting the baseline for advanced operations like hyperspectral filtering, beam steering or spatial-division multiplexing.
ExpPoint-MAE: Better interpretability and performance for self-supervised point cloud transformers

In this paper we delve into the properties of transformers, attained through self-supervision, in the point cloud domain. Specifically, we evaluate the effectiveness of Masked Autoencoding as a pretraining scheme, and explore Momentum Contrast as an alternative. In our study we investigate the impact of data quantity on the learned features, and uncover similarities in the transformer's behavior across domains. Through comprehensive visualiations, we observe that the transformer learns to attend to semantically meaningful regions, indicating that pretraining leads to a better understanding of the underlying geometry. Moreover, we examine the finetuning process and its effect on the learned representations. Based on that, we devise an unfreezing strategy which consistently outperforms our baseline without introducing any other modifications to the model or the training pipeline, and achieve state-of-the-art results in the classification task among transformer models.
Rethinking tipping points in spatial ecosystems

The theory of alternative stable states and tipping points has garnered a lot of attention in the last decades. It predicts potential critical transitions from one ecosystem state to a completely different state under increasing environmental stress. However, typically ecosystem models that predict tipping do not resolve space explicitly. As ecosystems are inherently spatial, it is important to understand the effects of incorporating spatial processes in models, and how those insights translate to the real world. Moreover, spatial ecosystem structures, such as vegetation patterns, are important in the prediction of ecosystem response in the face of environmental change. Models and observations from real savanna ecosystems and drylands have suggested that they may exhibit both tipping behavior as well as spatial pattern formation. Hence, in this paper, we use mathematical models of humid savannas and drylands to illustrate several pattern formation phenomena that may arise when incorporating spatial dynamics in models that exhibit tipping without resolving space. We argue that such mechanisms challenge the notion of large scale critical transitions in response to global change and reveal a more resilient nature of spatial ecosystems.
A Generic Closed-form Optimal Step-size for ADMM

In this work, we present a generic step-size choice for the ADMM type proximal algorithms. It admits a closed-form expression and is theoretically optimal with respect to a worst-case convergence rate bound. It is simply given by the ratio of Euclidean norms of the dual and primal solutions, i.e., $ ||{\lambda}^\star|| / ||{x}^\star||$. Numerical tests show that its practical performance is near-optimal in general. The only challenge is that such a ratio is not known a priori and we provide two strategies to address it. The derivation of our step-size choice is based on studying the fixed-point structure of ADMM using the proximal operator. However, we demonstrate that the classical proximal operator definition contains an input scaling issue. This leads to a scaled step-size optimization problem which would yield a false solution. Such an issue is naturally avoided by our proposed new definition of the proximal operator. A series of its properties is established.
Few-fermion systems in one dimension

This thesis reports on experiments with few-fermion systems in quasi one dimensional confining potentials with tunable interaction. Using ultracold atoms we prepare these systems in a well defined quantum state with fidelities of 90% for up to 8 particles. The interparticle interaction in the 1D environment can be effectively described by a 1D contact interaction where the coupling strength can be tuned with a confinement induced resonance (CIR). We investigate a system of two repulsively interacting distinguishable fermions and compare it to a system of two identical noninteracting fermions. For diverging coupling strength we show the fermionization of two distinguishable fermions, i.e. we observe the energy and the square modulus of the wavefunction of both system to be identical. We also perform radio frequency spectroscopy to measure the energy of a single minority particle interacting repulsively with a defined number of majority particles of different spin. We study the crossover from a few-particle system to a many-particle system by adding majority particles one by one. We observe that already four majority particles are enough to describe the properties of the minority by that of a polaron-like particle, i.e. by a single impurity dressed by a 1D Fermi sea. Investigating attractively interacting systems we observe that for increasing interaction strength the pair correlations in the system increases. This correlation leads to a strong odd-even effect of the single particle dissociation energy similar to the one observed for nuclei.
Improvement of Antioxidant Defences in Keratinocytes Grown in Physioxia: Comparison of 2D and 3D Models

Keratinocytes prevent skin photoaging by ensuring the defence against oxidative stress, an excessive production of reactive oxygen species (ROS). They are localized within the epidermis where the oxygen level (1-3% O2), named physioxia, is low compared to other organs. Oxygen is essential for life but also generates ROS. Most of the in vitro studies on keratinocyte antioxidant capacities are performed under atmospheric oxygen, named normoxia, which is very far from the physiological microenvironment, thus submitting cells to an overoxygenation. The present study is aimed at investigating the antioxidant status of keratinocyte grown under physioxia in both 2D and 3D models. First, we show that the basal antioxidant profiles of keratinocytes display important differences when comparing the HaCaT cell line, primary keratinocytes (NHEK), reconstructed epidermis (RHE), and skin explants. Physioxia was shown to promote a strong proliferation of keratinocytes in monolayers and in RHE, resulting in a thinner epidermis likely due to a slowdown in cell differentiation. Interestingly, cells in physioxia exhibited a lower ROS production upon stress, suggesting a better protection against oxidative stress. To understand this effect, we studied the antioxidant enzymes and reported a lower or equivalent level of mRNA for all enzymes in physioxia conditions compared to normoxia, but a higher activity for catalase and superoxide dismutases, whatever the culture model. The unchanged catalase amount, in NHEK and RHE, suggests an overactivation of the enzyme in physioxia, whereas the higher amount of SOD2 can explain the strong activity. Taken together, our results demonstrate the role of oxygen in the regulation of the antioxidant defences in keratinocytes, topic of particular importance for studying skin aging. Additionally, the present work points out the interest of the choice of both the keratinocyte culture model and the oxygen level to be as close as possible to the in situ skin.
Genetic polymorphism of the Dab2 gene and its association with Type 2 Diabetes Mellitus in the Chinese Uyghur population

Objective The human Disabled-2 (Dab2) protein is an endocytic adaptor protein, which plays an essential role in endocytosis of transmembrane cargo, including low-density lipoprotein cholesterol (LDL-C). As a candidate gene for dyslipidemia, Dab2 is also involved in the development of type 2 diabetes mellitus(T2DM). The aim of this study was to investigate the effects of genetic variants of the Dab2 gene on the related risk of T2DM in the Uygur and Han populations of Xinjiang, China. Methods A total of 2,157 age- and sex-matched individuals (528 T2DM patients and 1,629 controls) were included in this case-control study. Four high frequency SNPs (rs1050903, rs2255280, rs2855512 and rs11959928) of the Dab2 gene were genotyped using an improved multiplex ligation detection reaction (iMLDR) genotyping assay, and the forecast value of the SNP for T2DM was assessed by statistical analysis of clinical data profiles and gene frequencies. Results We found that in the Uygur population studied, for both rs2255280 and rs2855512, there were significant differences in the distribution of genotypes (AA/CA/CC), and the recessive model (CC vs. CA + AA) between T2DM patients and the controls (P < 0.05). After adjusting for confounders, the recessive model (CC vs. CA + AA) of both rs2255280 and rs2855512 remained significantly associated with T2DM in this population (rs2255280: OR = 5.303, 95% CI [1.236 to −22.755], P = 0.025; rs2855512: OR = 4.892, 95% CI [1.136 to −21.013], P = 0.033). The genotypes (AA/CA/CC) and recessive models (CC vs. CA + AA) of rs2855512 and rs2255280 were also associated with the plasma glucose and HbA1c levels (all P < 0.05) in this population. There were no significant differences in genotypes, all genetic models, or allele frequencies between the T2DM and control group in the Han population group (all P > 0.05). Conclusions The present study suggests that the variation of the Dab2 gene loci rs2255280 and rs2855512 is related to the incidence of T2DM in the Uygur population, but not in the Han population. In this study, these variations in Dab2 were an independent predictor for T2DM in the Uygur population of Xinjiang, China.
Microbial community in buckwheat rhizosphere with different nitrogen application rates

Microorganism plays a pivotal role in regulating sustainable development of agriculture. The excessive application of nitrogen fertilizer is considered to affect the microbial structure in many agricultural systems. The present study aimed to assess the impacts of nitrogen application rate on microbial diversity, community and functionality in rhizosphere of Tartary buckwheat in short-time. The nitrogen fertilizer was applied at rates of 90 kg (N90), 120 kg (N120) and 150 kg (N150) urea per hectare, respectively. The soil properties were measured chemical analysis and displayed no difference among treatments. Metagenome analysis results showed that the microbial diversity was not affected, but the microbial community and functionality were affected by the nitrogen application rate. According to the Linear discriminant analysis effect size (LEfSe) analysis, 15 taxa were significantly enriched in the N120 and N150 groups, no taxon was enriched in the N90 group. Kyoto Encyclopaedia of Genes and Genomes (KEGG) annotation results revealed that the genes related to butanoate and beta alanine metabolism were significantly enriched in the N90 group, the genes related to thiamine metabolism, lipopolysaccharide biosynthesis and biofilm formation were significantly enriched in the N120 group, and the genes related to neurodegenerative disease was significantly enriched in the N150 group. In conclusion, short-time nitrogen fertilizer application shifted the microbial community structure and functionality.
LncRNA AC040162.3 Promotes HCV-Induced T2DM Deterioration through the miRNA-223-3p/NLRP3 Molecular Axis

Background Diabetes is one of the most common diseases and major public health burdens worldwide. Type 2 diabetes mellitus (T2DM) is associated with chronic hepatitis C virus (HCV) infection, and lncRNAs play an important role in HCV-induced T2DM. We aimed to explore the effect of lncRNA AC040162.3 on HCV-induced T2DM. Methods HCV was used to infect MIN6 cells to establish an in vitro model. HCV copy number and miRNA expression were detected by Real Time Quantitative PCR (RT-qPCR). Enzyme-Linked Immunosorbent Assay (ELISA) was used to detect the secretion of insulin, and methyl thiazolyl tetrazolium (MTT) was applied to analyze cell viability. Apoptosis was analyzed by Western blotting and flow cytometry. In addition, Western blotting and TdT-mediated dUTP Nick End Labeling (TUNEL) were used to analyze pyroptosis. Luciferase reporter assays were used to investigate the targeting relationship. Results The expression of LncRNA AC040162.3 and NLRP3 was markedly increased in HCV–T2DM, while the expression of miR-223-3p was remarkably inhibited. In vitro experiments demonstrated that lncRNA AC040162.3 silencing or miR-223-3p overexpression remarkably alleviated HCV-induced T2DM deterioration by inhibiting cell apoptosis and pyroptosis and enhancing cell viability. We then demonstrated that silencing lncRNA AC040162.3 promoted the expression of miR-223-3p and that miR-223-3p bound to lncRNA AC040162.3 and the NLRP3 binding site. In addition, the protective effects of LncRNA AC040162.3 silencing in HCV-infected MIN6 cells were reversed by overexpression of NLRP3 or silencing of miR-223-3p. Conclusion Silencing of lncRNA AC040162.3 alleviates the process of HCV-induced T2DM by governing the miR-223-3p/NLRP3 axis.
Adverse events with quetiapine and clarithromycin coprescription: A population‐based retrospective cohort study

Quetiapine is an atypical antipsychotic predominantly metabolized by the cytochrome P450 3A4 (CYP3A4) enzyme. We studied the risk of adverse events following coprescription of clarithromycin (a strong CYP3A4 inhibitor) versus azithromycin (not a CYP3A4 inhibitor) in quetiapine users.
Existential Loneliness Among Older People from the Perspective of Health Care Professionals: A European Multicenter Study

Introduction Health care professionals (HCPs) encounter different forms of loneliness in their work. It is essential that they have the courage, skills, and tools to deal with loneliness, in particular with existential loneliness (EL) which relates to meaning in life and the fundamentals of living and dying. Aim The aim of this study was to investigate HCPs’ views on loneliness among older people and their understanding, perception, and professional experience of EL in older people. Materials and Methods In all, 139 HCPs from five European countries participated in audio-recorded focus group and individual interviews. The transcribed materials were locally analyzed using a predefined template. The participating countries’ results were then translated, merged, and inductively analyzed using conventional content analysis. Results Participants described different forms of loneliness – a negative form that is unwanted and causes suffering, and a positive form where solitude is desired and sought. The results showed that the HCPs’ knowledge and understanding of EL varied. The HCPs mainly related EL to different types of loss, eg loss of autonomy, independence, hope, and faith, and to concern alienation, guilt, regret and remorse, and concerns about the future. Discussion and Conclusions The HCPs expressed a need to improve their sensitivity and self-confidence to engage in existential conversations. They also stated the need to increase their knowledge and understanding of aging, death, and dying. Based on these results, a training program aimed to increase knowledge and understanding of older people’s situation has been developed. The program includes practical training in conversations about emotional and existential aspects, based on recurrent reflections on the topics presented. The program is available at: www.aloneproject. eu.
PID parameter optimization using T-S fuzzy adaptive particle swarm optimization

In order to solve the premature convergence problem of particle swarm optimization,a novel fuzzy adaptive Particle Swarm Optimization based on T-S mode(lT-SPSO) is presented.The proposed method shapes the T-S rules according to the cur- rent best performance evaluation and inertia weight of swarm,which dynamically update the value of inertia weight and signifi- cantly speed up the convergence.The improved algorithm significantly improves the performance of parameters applied in parame- ter setting of PID controller.The simulation results illustrate the effectiveness of this proposed method and superiority of the controller.