Miracle-dz/UniFAR-FTUs huggingface dataset:
Verification of the efficacy of topical sirolimus gel for systemic rare vascular malformations: a pilot study

Numerous clinical trials of sirolimus, an inhibitor of mechanistic/mammalian target of rapamycin complex 1, for the treatment of vascular malformations have been conducted. However, aside from lymphatic malformations, the efficacy of sirolimus for venous and capillary malformations has not been established. Moreover, no generalized venous or capillary malformations have been treated with topical sirolimus. To evaluate the safety and efficacy of topical sirolimus for venous and capillary malformations and to compare the efficacy of topical and systemic sirolimus therapy, an open‐label single‐arm pilot study with 0.2% sirolimus gel was conducted from July 19, 2019, to January 30, 2020, in four patients diagnosed with different vascular malformations (blue rubber bleb nevus syndrome, common venous malformation, phakomatosis pigmentovascularis type IVb, and angiokeratoma in Fabry disease). The primary endpoint was the safety evaluation of sirolimus gel. The main secondary endpoint was the improvement rate evaluated by the Central Judgment Committee at 12 weeks using photographs. No adverse events were observed. Blood sirolimus was not detected in any patient. Two patients (50%) had mild improvement, and the remaining two patients (50%) showed no change after 12 weeks of treatment. Blue rubber bleb nevus syndrome, a generalized venous malformation, showed the greatest response. In conclusion, 0.2% sirolimus gel was found to be as clinically effective as systemic sirolimus treatment in patients with venous and capillary malformations and more effective for early active lesions, even systemic venous malformations.
Studi Sesar Aktif, Kinematik, dan Dinamik Zona Sesar Kaligarang (KGFZ) di Semarang

Deformasi di Kota Semarang menyebabkan sesar aktif. Identifikasi sesar dan struktur penyerta yang tepat akan memberikan pemahaman kinematik dan dinamik dari proses tektonik di Kota Semarang. Penelitian ini membahas tentang kinematik dan dinamik sesar Kaligarang serta membuktikan apakah sesar Kaligarang merupakan sesar aktif dengan pendekatan morfometri dan morfotektonik. Dinamik sesar Kaligarang memberikan penjelasan arah tegasan utama yang membentuk sesar tersebut.
Large-scale sea ice–Surface temperature variability linked to Atlantic meridional overturning circulation

Due to its involvement in numerous feedbacks, sea ice plays a crucial role not only for polar climate but also at global scale. We analyse state-of-the-art observed, reconstructed, and modelled sea-ice concentration (SIC) together with sea surface temperature (SST) to disentangle the influence of different forcing factors on the variability of these coupled fields. Canonical Correlation Analysis provides distinct pairs of coupled Arctic SIC–Atlantic SST variability which are linked to prominent oceanic and atmospheric modes of variability over the period 1854–2017. The first pair captures the behaviour of the Atlantic meridional overturning circulation (AMOC) while the third and can be associated with the North Atlantic Oscillation (NAO) in a physically consistent manner. The dominant global SIC–Atlantic SST coupled mode highlights the contrast between the responses of Arctic and Antarctic sea ice to changes in AMOC over the 1959–2021 period. Model results indicate that coupled SST–SIC patterns can be associated with changes in ocean circulation. We conclude that a correct representation of AMOC-induced coupled SST–SIC variability in climate models is essential to understand the past, present and future sea-ice evolution.
A trial-based economic evaluation of the CaFaSpA referral strategy for axial spondyloarthritis

Objective To assess the cost–utility from healthcare and societal perspectives of the digital CaFaSpA referral strategy (CS) for axial spondyloarthritis (axSpA) in primary care patients with chronic low back pain (CLBP). Method A cluster randomized controlled trial was performed in the Netherlands. General practice units were randomized into CS or usual care (UC). Economic evaluation was performed from the healthcare and societal perspectives within a 12-month time horizon. Outcome measures encompassed disability [Roland–Morris Disability Questionnaire (RMDQ)] and health-related quality of life (EQ-5D-3L). Direct medical (iMTA Medical Consumption Questionnaire) and indirect costs (iMTA Productivity Cost Questionnaire), including productivity loss, were evaluated. Incremental cost–utility ratios (ICURs) were calculated. Results The study included 90 GP clusters with 563 patients (CS: n = 260; UC: n = 303) (mean ± sd age 36.3 ± 7.5 years; 66% female). After 12 months, no minimal important differences in outcomes were observed for RMDQ (−0.21, 95%CI −1.52 to 1.13) or EQ-5D (−0.02, 95%CI −0.08 to 0.05). However, total costs were significantly lower in the CS group owing to lower productivity loss costs. The ICUR for RMDQ was €18,059 per point decrease and €220,457 per quality-adjusted life year increase. Conclusions Digital referral did not decrease the overall healthcare status of patients after 1 year of follow-up and appears to be more cost-effective than UC. Therefore, CS can be used as an appropriate primary care referral model for CLBP patients at risk for axSpA. This will accelerate timely provision of care by the right caregiver.
Deep Video Codec Control for Vision Models

Standardized lossy video coding is at the core of almost all real-world video processing pipelines. Rate control is used to enable standard codecs to adapt to different network bandwidth conditions or storage constraints. However, standard video codecs (e.g., H.264) and their rate control modules aim to minimize video distortion w.r. t human quality assessment. We demonstrate empirically that standard-coded videos vastly deteriorate the performance of deep vision models. To overcome the deterioration of vision performance, this paper presents the first end-to-end learnable deep video codec control that considers both bandwidth constraints and downstream deep vision performance, while adhering to existing standardization. We demonstrate that our approach better preserves downstream deep vision performance than traditional approaches.
Bi-level iterative regularization for inverse problems in nonlinear PDEs

We investigate the ill-posed inverse problem of recovering unknown spatially dependent parameters in nonlinear evolution PDEs. We propose a bi-level Landweber scheme, where the upper-level parameter reconstruction embeds a lower-level state approximation. This can be seen as combining the classical reduced setting and the newer all-at-once setting, allowing us to, respectively, utilize well-posedness of the parameter-to-state map, and to bypass having to solve nonlinear PDEs exactly. Using this, we derive stopping rules for lower- and upper-level iterations and convergence of the bi-level method. We discuss application to parameter identification for the Landau-Lifshitz-Gilbert equation in magnetic particle imaging.
Strong quantum nonlocality with genuine entanglement in an 
N
-qutrit system

In this paper, we construct genuinely multipartite entangled bases in $(\mathbb{C}^{3})^{\otimes N}$ for $N\geq3$, where every state is one-uniform state. By modifying this construction, we successfully obtain strongly nonlocal orthogonal genuinely entangled sets and strongly nonlocal orthogonal genuinely entangled bases, which provide an answer to the open problem raised by Halder $et~al.$ [\href{https://journals.aps. org/prl/abstract/10.1103/PhysRevLett.122. 040403} {Phy. Rev. Lett. \textbf{122}, 040403 (2019)}]. The strongly nonlocal orthogonal genuine entangled set we constructed in $(\mathbb{C}^{3})^{\otimes N}$ contains much fewer quantum states than all known ones. When $N>3$, our result answers the open question given by Wang $et~al$. [\href{https://journals.aps. org/pra/abstract/10.1103/PhysRevA.104. 012424} {Phys. Rev. A \textbf{104}, 012424 (2021)}].
Validation of the Fatty Liver Index for identifying non‐alcoholic fatty liver disease in a Kenyan population

Fatty Liver Index (FLI) is a simple clinical scoring system estimating non‐alcoholic fatty liver disease (NAFLD). It is validated in European‐descent and Asian populations, but not in sub‐Saharan Africans. The aim of this study is to evaluate the validity of the FLI for predicting NAFLD in a population from Kenya.
Variables Associated with Emotional Symptom Severity in Primary Care Patients: The Usefulness of a Logistic Regression Equation to Help Clinical Assessment and Treatment Decisions

Abstract The aim of this study is to contribute to the evidence regarding variables related to emotional symptom severity and to use them to exemplify the potential usefulness of logistic regression for clinical assessment at primary care, where most of these disorders are treated. Cross-sectional data related to depression and anxiety symptoms, sociodemographic characteristics, quality of life (QoL), and emotion-regulation processes were collected from 1,704 primary care patients. Correlation and analysis of variance (ANOVA) tests were conducted to identify those variables associated with both depression and anxiety. Participants were then divided into severe and nonsevere emotional symptoms, and binomial logistic regression was used to identify the variables that contributed the most to classify the severity. The final adjusted model included psychological QoL (p < .001, odds ratio [OR] = .426, 95% CI [.318, .569]), negative metacognitions (p < .001, OR = 1.083, 95% CI [1.045, 1.122]), physical QoL (p < .001, OR = .870, 95% CI [.841, .900]), brooding rumination (p < .001, OR = 1.087, 95% CI [1.042, 1.133]), worry (p < .001, OR = 1.047, 95% CI [1.025, 1.070]), and employment status (p = .022, OR [.397, 2.039]) as independent variables, ρ2 = . 326, area under the curve (AUC) = . 857. Moreover, rumination and psychological QoL emerged as the best predictors to form a simplified equation to determine the emotional symptom severity (ρ2 = .259, AUC = .822). The use of statistical models like this could accelerate the assessment and treatment-decision process, depending less on the subjective point of view of clinicians and optimizing health care resources.
Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning

Affordable 3D scanners often produce sparse and non-uniform point clouds that negatively impact downstream applications in robotic systems. While existing point cloud upsampling architectures have demonstrated promising results on standard benchmarks, they tend to experience significant performance drops when the test data have different distributions from the training data. To address this issue, this paper proposes a test-time adaption approach to enhance model generality of point cloud upsampling. The proposed approach leverages meta-learning to explicitly learn network parameters for test-time adaption. Our method does not require any prior information about the test data. During meta-training, the model parameters are learned from a collection of instance-level tasks, each of which consists of a sparse-dense pair of point clouds from the training data. During meta-testing, the trained model is fine-tuned with a few gradient updates to produce a unique set of network parameters for each test instance. The updated model is then used for the final prediction. Our framework is generic and can be applied in a plug-and-play manner with existing backbone networks in point cloud upsampling. Extensive experiments demonstrate that our approach improves the performance of state-of-the-art models.
Distributed energy-balance glacier melt-modelling in the Donjek Range of the St. Elias Mountains, Yukon Territory, Canada: model transferability in space and time

Modelling melt from glaciers is crucial to assessing regional hydrology and eustatic sea-level rise. To investigate melt-model transferability, a distributed energy-balance melt model (DEBM) is applied to two glaciers of opposing aspects in the Donjek Range of the St. Elias Mountains, Yukon Territory, Canada. An analysis is conducted in four stages to assess the transferability of the DEBM in space and time: (1) locally derived model parameter values and meteorological forcing variables are used to assess model skill; (2) model parameter values are transferred between glacier sites and between years of study; (3) measured meteorological forcing variables are transfered between glaciers, using locally derived parameter values; (4) both model parameter values and measured meteorological forcing variables are transfered from one glacier site to the other, treating the second glacier site as an extension of the first. The model has high transferability in time, but has limited transferability in space.
Fault Injection on Embedded Neural Networks: Impact of a Single Instruction Skip

With the large-scale integration and use of neural network models, especially in critical embedded systems, their security assessment to guarantee their reliability is becoming an urgent need. More particularly, models deployed in embed-ded platforms, such as 32-bit microcontrollers, are physically accessible by adversaries and therefore vulnerable to hardware disturbances. We present the first set of experiments on the use of two fault injection means, electromagnetic and laser injections, applied on neural networks models embedded on a Cortex M4 32-bit microcontroller platform. Contrary to most of state-of-the-art works dedicated to the alteration of the internal parameters or input values, our goal is to simulate and experimentally demonstrate the impact of a specific fault model that is instruction skip. For that purpose, we assessed several modification attacks on the control flow of a neural network inference. We reveal integrity threats by targeting several steps in the inference program of typical convolutional neural network models, which may be exploited by an attacker to alter the predictions of the target models with different adversarial goals.
A Posteriori Analysis and Adaptive Algorithms for Blended Type Atomistic-to-Continuum Coupling with Higher-Order Finite Elements

The efficient and accurate simulation of material systems with defects using atomistic- to-continuum (a/c) coupling methods is a topic of considerable interest in the field of computational materials science. To achieve the desired balance between accuracy and computational efficiency, the use of a posteriori analysis and adaptive algorithms is critical. In this work, we present a rigorous a posteriori error analysis for three typical blended a/c coupling methods: the blended energy-based quasi-continuum (BQCE) method, the blended force-based quasi-continuum (BQCF) method, and the atomistic/continuum blending with ghost force correction (BGFC) method. We employ first and second-order finite element methods (and potentially higher-order methods) to discretize the Cauchy-Born model in the continuum region. The resulting error estimator provides both an upper bound on the true approximation error and a lower bound up to a theory-based truncation indicator, ensuring its reliability and efficiency. Moreover, we propose an a posteriori analysis for the energy error. We have designed and implemented a corresponding adaptive mesh refinement algorithm for two typical examples of crystalline defects. In both numerical experiments, we observe optimal convergence rates with respect to degrees of freedom when compared to a priori error estimates.
The awakening of dormant neuronal precursors in the adult and aged brain

Beyond the canonical neurogenic niches, there are dormant neuronal precursors in several regions of the adult mammalian brain. Dormant precursors maintain persisting post‐mitotic immaturity from birth to adulthood, followed by staggered awakening, in a process that is still largely unresolved. Strikingly, due to the slow rate of awakening, some precursors remain immature until old age, which led us to question whether their awakening and maturation are affected by aging. To this end, we studied the maturation of dormant precursors in transgenic mice (DCX‐CreERT2/flox‐EGFP) in which immature precursors were labelled permanently in vivo at different ages. We found that dormant precursors are capable of awakening at young age, becoming adult‐matured neurons (AM), as well as of awakening at old age, becoming late AM. Thus, protracted immaturity does not prevent late awakening and maturation. However, late AM diverged morphologically and functionally from AM. Moreover, AM were functionally most similar to neonatal‐matured neurons (NM). Conversely, late AM were endowed with high intrinsic excitability and high input resistance, and received a smaller amount of spontaneous synaptic input, implying their relative immaturity. Thus, late AM awakening still occurs at advanced age, but the maturation process is slow.
Reduction of Frobenius extriangulated categories

We describe a reduction technique for stably 2-Calabi--Yau Frobenius extriangulated categories $\mathcal{F}$ with respect to a functorially finite rigid subcategory $\mathcal{X}$. The reduction of such a category is another category $\mathcal{X}^{\perp_1}\subseteq\mathcal{F}$ of the same kind, whose cluster-tilting subcategories are those cluster-tilting subcategories $\mathcal{T}\subseteq\mathcal{F}$ such that $\mathcal{X}\subseteq\mathcal{T}$. This reduction operation generalises Iyama--Yoshino's reduction for 2-Calabi--Yau triangulated categories, which is recovered by passing to stable categories. Moreover, for a certain class of categories $\mathcal{F}$ and rigid objects $M$, we show that the relationship between $\mathcal{F}$ and $M^{\perp_1}$ may also be expressed in terms of internally Calabi--Yau algebras, in the sense of the third author. As an application, we give a conceptual proof of a result on frieze patterns originally obtained by the first author with Baur, Gratz, Serhiyenko, and Todorov.
A long trend of sexually transmitted diseases before and after the COVID-19 pandemic in China (2010-21).

BACKGROUND The longer ongoing benefits of coronavirus disease 2019 (COVID-19) non-pharmaceutical interventions (NPIs) for sexually transmitted diseases (STDs) in China are still unclear. We aimed to explore the changes in five STDs (AIDS, hepatitis B, hepatitis C, gonorrhoea, and syphilis) before, during, and after the COVID-19 pandemic in mainland China, from 2010 to 2021. METHODS The number of the monthly reported cases of the five STDs were extracted from the website to construct the Joinpoint regression and autoregressive integrated moving average (ARIMA) models. Eight indicators reflecting NPIs were chosen from the COVID-19 Government Response Tracker system. The STDs and eight indicators were used to establish the Multivariable generalised linear model (GLM) to calculate the incidence rate ratios (IRRs). RESULTS With the exception of hepatitis B, the other four STDs (AIDS, hepatitis C, gonorrhoea, and syphilis) had a positive average annual percent change over the past 12years. All the ARIMA models had passed the Ljung-Box test, and the predicted data fit well with the data from 2010 to 2019. All five STDs were significantly reduced in 2020 compared with 2019, with significant estimated IRRs ranging from 0.88 to 0.92. In the GLM, using data for the years 2020 (February-December) and 2021, the IRRs were not significant after adjusting for the eight indicators in multivariate analysis. CONCLUSION Our study demonstrated that the incidence of the five STDs decreased rapidly during the COVID-19 pandemic in 2020. A recovery of STDs in 2021 was found to occur compared with that in 2020, but the rising trend disappeared after adjusting for the NPIs. Our study demonstrated that NPIs have an effect on STDs, but the relaxation of NPI usage might lead to a resurgence.
Internal structures of a subaerial dacite cryptodome at Usu volcano, Hokkaido, Japan (特集 2003年度実施の地域との共同研究の報告)

A partly eroded, subaerial, dacite cryptodome at Showa-Shinzan, Usu volcano, Hokkaido, Japan, displays its internal structures, and provides an excellent opportunity to study contact relationship between cryptodome and overlying sediment. The margin of the cryptodome comprises two facies: inner coherent dacite and outer dacite breccia. The coherent dacite facies is ~5 m in the exposed section, and consists of homogeneous or weakly flow-banded, feldspar-phyric dacite. The dacite breccia facies envelope the coherent dacite facies, and is 4-5 m thick. The breccia is monomictic, non-stratified and consists of angular dacite clasts up to 15 cm across in a cogenetic matrix. The overlying sediment directly covers the dacite breccia facies, and comprises reddishbrown, fluvial deposit. The dacite breccia formed by fracturing of coherent dacite in response to cooling contraction, and shearing of the fractured dacite due to movement of the growing cryptodome.
Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs

In this article, the optimal sample complexity of learning the underlying interaction/dependencies of a Linear Dynamical System (LDS) over a Directed Acyclic Graph (DAG) is studied. The sample complexity of learning a DAG's structure is well-studied for static systems, where the samples of nodal states are independent and identically distributed (i.i.d.). However, such a study is less explored for DAGs with dynamical systems, where the nodal states are temporally correlated. We call such a DAG underlying an LDS as \emph{dynamical} DAG (DDAG). In particular, we consider a DDAG where the nodal dynamics are driven by unobserved exogenous noise sources that are wide-sense stationary (WSS) in time but are mutually uncorrelated, and have the same {power spectral density (PSD)}. Inspired by the static settings, a metric and an algorithm based on the PSD matrix of the observed time series are proposed to reconstruct the DDAG. The equal noise PSD assumption can be relaxed such that identifiability conditions for DDAG reconstruction are not violated. For the LDS with WSS (sub) Gaussian exogenous noise sources, it is shown that the optimal sample complexity (or length of state trajectory) needed to learn the DDAG is $n=\Theta(q\log(p/q))$, where $p$ is the number of nodes and $q$ is the maximum number of parents per node. To prove the sample complexity upper bound, a concentration bound for the PSD estimation is derived, under two different sampling strategies. A matching min-max lower bound using generalized Fano's inequality also is provided, thus showing the order optimality of the proposed algorithm.
SNAP-25, but not SNAP-23, is essential for photoreceptor function and survival in mice

Vesicular transport plays critical roles in photopigment delivery at photoreceptor outer segments and glutamate exocytosis at photoreceptor synapses. Previous studies into the role of photoreceptor SNAP proteins are limited in their characterizations into only gene/protein expression and do not delve further into their functional role. Here, we examine the expression and localization of SNAP-23 and SNAP-25 mRNA and protein. Using SNAP-23 and SNAP-25 conditional knockout mice, we further evaluated the morphological and functional consequences that the absence of these proteins has on vision. Although we found that the ubiquitously expressed SNAP-23 showed weak mRNA expression in photoreceptors, removal of SNAP-23 did not result in any observable phenotype. We found that neuronal SNAP-25 is developmentally regulated and SNAP-25 mRNA undergoes mRNA trafficking to the photoreceptor inner segments coinciding with the development of photoreceptor outer segments. Removal of SNAP-25 in photoreceptor cells led to changes in both outer segment protein trafficking and synaptic integrity, resulting in a complete loss of vision in SNAP-25 cKO mice. Our results conclude that SNAP-25, but not SNAP-23, is the essential isoform for photoreceptor survival and function.