Miracle-dz/UniFAR-FTUs huggingface dataset:
CrossGLG: LLM Guides One-shot Skeleton-based 3D Action Recognition in a Cross-level Manner

Most existing one-shot skeleton-based action recognition focuses on raw low-level information (e.g., joint location), and may suffer from local information loss and low generalization ability. To alleviate these, we propose to leverage text description generated from large language models (LLM) that contain high-level human knowledge, to guide feature learning, in a global-local-global way. Particularly, during training, we design $2$ prompts to gain global and local text descriptions of each action from an LLM. We first utilize the global text description to guide the skeleton encoder focus on informative joints (i.e.,global-to-local). Then we build non-local interaction between local text and joint features, to form the final global representation (i.e., local-to-global). To mitigate the asymmetry issue between the training and inference phases, we further design a dual-branch architecture that allows the model to perform novel class inference without any text input, also making the additional inference cost neglectable compared with the base skeleton encoder. Extensive experiments on three different benchmarks show that CrossGLG consistently outperforms the existing SOTA methods with large margins, and the inference cost (model size) is only $2.8$\% than the previous SOTA. CrossGLG can also serve as a plug-and-play module that can substantially enhance the performance of different SOTA skeleton encoders with a neglectable cost during inference. The source code will be released soon.
Insertion of percutaneous endoscopic gastrostomy tubes with jejunal extensions using the “wedge” technique: a novel method to prevent retrograde tube migration into the stomach

Abstract Background and study aim In percutaneous endoscopic gastrostomy (PEG) with jejunal extension (PEGJ) procedures, retrograde migration of the jejunal extension tube into the stomach during endoscope withdrawal is a frustrating problem. We describe the novel “wedge” technique for inserting the jejunal extension tube, utilizing single-balloon enteroscopy to anchor it in place. Patients and methods Prospective 1-year study of consecutive patients undergoing PEGJ insertion at a single tertiary care center. The primary outcome was number of pyloric intubations required to place the jejunal extension tube. Secondary outcomes included success rate, time, and complications related to jejunal extension tube insertion. Results 17 patients underwent the procedure. The jejunal extension tube was inserted at the first attempt in 15 patients (88.2 %) and 2 required another pyloric intubation. Abdominal X-ray showed that all PEGJ tubes were successfully seated in the proximal jejunum. The mean (SD) time required for jejunal extension insertion was 16.9 (8.6) minutes. Two adverse events occurred due to PEG insertion although none were related to the jejunal extension insertion itself. Conclusions: The “wedge” technique is an effective and easy method for inserting a jejunal extension tube after PEG insertion.
Assessing Photoreceptor Structure in Retinitis Pigmentosa and Usher Syndrome

Purpose The purpose of this study was to examine cone photoreceptor structure in retinitis pigmentosa (RP) and Usher syndrome using confocal and nonconfocal split-detector adaptive optics scanning light ophthalmoscopy (AOSLO). Methods Nineteen subjects (11 RP, 8 Usher syndrome) underwent ophthalmic and genetic testing, spectral-domain optical coherence tomography (SD-OCT), and AOSLO imaging. Split-detector images obtained in 11 subjects (7 RP, 4 Usher syndrome) were used to assess remnant cone structure in areas of altered cone reflectivity on confocal AOSLO. Results Despite normal interdigitation zone and ellipsoid zone appearance on OCT, foveal and parafoveal cone densities derived from confocal AOSLO images were significantly lower in Usher syndrome compared with RP. This was due in large part to an increased prevalence of non-waveguiding cones in the Usher syndrome retina. Although significantly correlated to best-corrected visual acuity and foveal sensitivity, cone density can decrease by nearly 38% before visual acuity becomes abnormal. Aberrantly waveguiding cones were noted within the transition zone of all eyes and corresponded to intact inner segment structures. These remnant cones decreased in density and increased in diameter across the transition zone and disappeared with external limiting membrane collapse. Conclusions Foveal cone density can be decreased in RP and Usher syndrome before visible changes on OCT or a decline in visual function. Thus, AOSLO imaging may allow more sensitive monitoring of disease than current methods. However, confocal AOSLO is limited by dependence on cone waveguiding, whereas split-detector AOSLO offers unambiguous and quantifiable visualization of remnant cone inner segment structure. Confocal and split-detector thus offer complementary insights into retinal pathology.
Insight into the possible mechanism of the summer diapause of Delia antiqua (Diptera: Anthomyiidae) through digital gene expression analysis

The onion fly, Delia antiqua, is a major underground agricultural pest that can enter pupal diapause in the summer and winter seasons. However, little is known about its molecular regulation due to the lack of genomic resources. To gain insight into the possible mechanism of summer diapause (SD), high‐throughput RNA‐Seq data were generated from non‐diapause (ND) and SD (initial, maintenance and quiescence phase) pupae. Three pair‐wise comparisons were performed and identified, 1380, 1471 and 435, and were significantly regulated transcripts. Further analysis revealed that the enrichment of several functional terms related to juvenile hormone regulation, cell cycle, carbon hydrate and lipid metabolism, innate immune and stress responses, various signalling transductions, ubiquitin‐dependent proteosome, and variation in cuticular and cytoskeleton components were found between ND and SD and between different phases of SD. Global characterization of transcriptome profiling between SD and ND contributes to the in‐depth elucidation of the molecular mechanism of SD. Our results also offer insights into the evolution of insect diapause and support the importance of using the onion fly as a model to compare the molecular regulation events of summer and winter diapauses.
On Unsupervised Image-to-image translation and GAN stability

The problem of image-to-image translation is one that is intruiging and challenging at the same time, for the impact potential it can have on a wide variety of other computer vision applications like colorization, inpainting, segmentation and others. Given the high-level of sophistication needed to extract patterns from one domain and successfully applying them to another, especially, in a completely unsupervised (unpaired) manner, this problem has gained much attention as of the last few years. It is one of the first problems where successful applications to deep generative models, and especially Generative Adversarial Networks achieved astounding results that are actually of realworld impact, rather than just a show of theoretical prowess; the such that has been dominating the GAN world. In this work, we study some of the failure cases of a seminal work in the field, CycleGAN [1] and hypothesize that they are GAN-stability related, and propose two general models to try to alleviate these problems. We also reach the same conclusion of the problem being ill-posed that has been also circulating in the literature lately.
chaoptin, prominin, eyes shut and crumbs form a genetic network controlling the apical compartment of Drosophila photoreceptor cells

ABSTRACT The apical surface of epithelial cells is often highly specialised to fulfil cell type-specific functions. Many epithelial cells expand their apical surface by forming microvilli, actin-based, finger-like membrane protrusions. The apical surface of Drosophila photoreceptor cells (PRCs) forms tightly packed microvilli, which are organised into the photosensitive rhabdomeres. As previously shown, the GPI-anchored adhesion protein Chaoptin is required for the stability of the microvilli, whereas the transmembrane protein Crumbs is essential for proper rhabdomere morphogenesis. Here we show that chaoptin synergises with crumbs to ensure optimal rhabdomere width. In addition, reduction of crumbs ameliorates morphogenetic defects observed in PRCs mutant for prominin and eyes shut, known antagonists of chaoptin. These results suggest that these four genes provide a balance of adhesion and anti-adhesion to maintain microvilli development and maintenance. Similar to crumbs mutant PRCs, PRCs devoid of prominin or eyes shut undergo light-dependent retinal degeneration. Given the observation that human orthologues of crumbs, prominin and eyes shut result in progressive retinal degeneration and blindness, the Drosophila eye is ideally suited to unravel the genetic and cellular mechanisms that ensure morphogenesis of PRCs and their maintenance under light-mediated stress.
Physical change in cytoplasmic messenger ribonucleoproteins in cells treated with inhibitors of mRNA transcription

Exposure of intact cells to UV light brings about cross-linking of polyadenylated mRNA to a set of cytoplasmic proteins which are in direct contact with the mRNA in vivo. Substantial amounts of an additional protein of molecular weight 38,000 (38K) become cross-linked to the mRNA when cells are treated with inhibitors of mRNA synthesis (actinomycin D, camptothecin, and 5,6-dichloro-1-beta-D-ribofuranosyl benzimidazole) or after infection with vesicular stomatitis virus. Cordycepin, which inhibits polyadenylation but not mRNA synthesis, has no such effect. Inhibitors of protein synthesis and of rRNA synthesis are also without effect on 38K cross-linking to mRNA. The onset of the effect of inhibitors of mRNA synthesis on the UV cross-linkable interaction between mRNA and 38K is rapid and reaches a maximal level in less than 60 min, and it is completely and rapidly reversible. In cells treated with actinomycin D, the amount of 38K which becomes cross-linked to mRNA is proportional to the extent of inhibition of mRNA synthesis. The association of 38K with mRNA during transcriptional arrest does not require protein synthesis because simultaneous treatment with the protein synthesis inhibitor emetine does not interfere with it. The effectors which promote the interaction of 38K with mRNA do not affect the proteins which are in contact with polyadenylated heterogeneous nuclear RNA and do not markedly affect protein synthesis in the cell. The 38K protein can be isolated with the polyribosomal polyadenylated fraction from which it was purified, and monoclonal antibodies against it were prepared. Immunofluorescence microscopy shows mostly cytoplasmic and some nuclear staining. These observations demonstrate that commonly used inhibitors of transcription affect the physical state of messenger ribonucleoproteins in vivo.
Global potential energy surface, vibrational spectrum, and reaction dynamics of the first excited (Ã (2)A(')) state of HO(2).

The authors report extensive high-level ab initio studies of the first excited (Ã (2)A(')) state of HO(2). A global potential energy surface (PES) was developed by spline-fitting 17 000 ab initio points at the internal contracted multireference configuration interaction (icMRCI) level with the AVQZ basis set. To ascertain the spectroscopic accuracy of the PES, the near-equilibrium region of the molecule was also investigated using three interpolating moving least-squares-based PESs employing dynamically weighted icMRCI methods in the complete basis set limit. Vibrational energy levels on all four surfaces agree well with each other and a new assignment of some vibrational features is proposed. In addition, the dynamics of both the forward and reverse directions of the H+O(2)(ã (1)Δ(g))↔OH+O reaction (J=0) were studied using an exact wave packet method. The reactions are found to be dominated by sharp resonances.
Spin and Orbital Magnetism by Light in Rutile Altermagnets

While the understanding of altermagnetism is still at a very early stage, it is expected to play a role in various fields of condensed matter research, for example spintronics, caloritronics and superconductivity. In the field of optical magnetism, it is still unclear to which extent altermagnets as a class can exhibit a distinct behavior. Here we choose RuO$_2$, a prototype metallic altermagnet with a giant spin splitting, and CoF$_2$, an experimentally known insulating altermagnet, to study the light-induced magnetism in rutile altermagnets from first-principles. We demonstrate that in the non-relativisic limit the allowed sublattice-resolved orbital response exhibits symmetries, imposed by altermagnetism, which lead to a drastic canting of light-induced moments. On the other hand, we find that inclusion of spin-orbit interaction enhances the overall effect drastically, introduces a significant anisotropy with respect to the light polarization and strongly suppresses the canting of induced moments. Remarkably, we observe that the moments induced by linearly-polarized laser pulses in light altermagnets can even exceed in magnitude those predicted for heavy ferromagnets exposed to circularly polarized light. By resorting to microscopic tools we interpret our results in terms of the altermagnetic spin splittings and of their reciprocal space distribution. Based on our findings, we speculate that optical excitations may provide a unique tool to switch and probe the magnetic state of rutile altermagnets.
Towards Adversarially Robust Dataset Distillation by Curvature Regularization

Dataset distillation (DD) allows datasets to be distilled to fractions of their original size while preserving the rich distributional information so that models trained on the distilled datasets can achieve a comparable accuracy while saving significant computational loads. Recent research in this area has been focusing on improving the accuracy of models trained on distilled datasets. In this paper, we aim to explore a new perspective of DD. We study how to embed adversarial robustness in distilled datasets, so that models trained on these datasets maintain the high accuracy and meanwhile acquire better adversarial robustness. We propose a new method that achieves this goal by incorporating curvature regularization into the distillation process with much less computational overhead than standard adversarial training. Extensive empirical experiments suggest that our method not only outperforms standard adversarial training on both accuracy and robustness with less computation overhead but is also capable of generating robust distilled datasets that can withstand various adversarial attacks.
Are Reservations Recommended?

We examine the role of reservations in capacity-constrained services with a focus on restaurants. Although customers value reservations, restaurants typically neither charge for them nor impose penalties for failing to keep them. However, reservations impose costs on firms offering them. We offer a novel motivation for offering reservations that emphasizes the way in which reservations can alter customer behavior. We focus on a market in which demand is uncertain and the firm has limited capacity. There is a positive chance that the firm will not have enough capacity to serve all potential customers. Customers are unable to observe how many potential diners are in the market before incurring a cost to request service. Hence, if reservations are not offered, some may choose to stay home rather than risk being denied service. This lowers the firm's sales when realized demand is low. Reservations increase sales on a slow night by guaranteeing reservations holders service. However, some reservation holders may choose not to use their reservations resulting in no-shows. The firm must then trade off higher sales in a soft market with sales lost to no-shows on busy nights. We consequently evaluate various no-show mitigation strategies, all of which serve to make reservations more likely in equilibrium. Competition also makes reservations more attractive; when there are many small firms in the market, reservations are always offered.
Spatial Dependence of the Growth Factor in Scalar-Tensor Cosmology

Scalar-tensor theories have taken on a key role in attempts to confront the growing open questions in standard cosmology. It is important to understand entirely their dynamics at perturbative level including any possible spatial dependence in their growth of large scale structures. In this work, we investigate the spatial dependence of the growth rate of scalar-tensor theories through the M\'{e}sz\'{a}ros equation. We confirm that at subhorizon level this dependence does not play a major role for viable models. However, we establish conditions on which this criterion is met which may be important for developing new models. In our work, we consider three specific models that exhibit spatial dependence of the growth rate at superhorizon modes, which may also be important for early Universe models.
Polarized Charge Dynamics of a Novel Charge Density Wave in Kagome FeGe

We report on the charge dynamics of kagome FeGe, an antiferromagnet with a charge density wave (CDW) transition at $T_{\mathrm{CDW}} \simeq 105$ K, using polarized infrared spectroscopy and band structure calculations. We reveal a pronounced optical anisotropy, various excitations associated with flat bands and van Hove singularities (VHSs), and a moderate level of electronic correlations. Notably, there are two types of remarkable spectral weight (SW) redistributions for above and below $T_{\mathrm{CDW}}$. The former involves a transfer between incoherent and coherent excitations driven by the magnetic splitting-induced elevation of flat bands. The latter manifests itself as a sudden change of SW from low to high energies for both $a$ and $c$ directions, suggesting a first-order transition and the three-dimensional nature of CDW. These anomalies in SW significantly differ from those observed in other kagome metals like CsV$_3$Sb$_5$, where the nesting of VHSs results in a pronounced CDW gap feature. Instead, our findings can be accounted for by the jump of VHSs relative to the Fermi energy via a first-order structural transition involving large partial Ge1-dimerization. Our study thus unveils a complex interplay among structure, magnetism, electronic correlations, and charge order in FeGe, offering valuable insights for a comprehensive understanding of CDW order in kagome systems.
Women's knowledge of and attitude towards organized cervical smear screening

OBJECTIVE To describe women's barriers to cervical screening by asking about their experience with and knowledge of smear tests and by examining the women's contact and relationship with their GP. SETTING Questionnaires sent to women in Aarhus County, Denmark. METHODS A case control study in a cohort. The cohort, 133,500 women, represents women aged 23-60 years who were invited to the organized cervical screening program between 1.10. 90 and 1.4. 94. A case group, non-attenders (n=694), who had not had a smear within the previous 42 months, and a control group, attenders (n=1131), who had at least one smear test within the previous 42 months, were compared with each other. Predictor variables in the two groups were analyzed by univariate and multivariate (logistic regression) analysis. RESULTS Non-attenders more often had insufficient contact with the GP (having a bad relationship, feeling of not receiving sufficient information) and associated a gynecological examination with more psychological unpleasantness. Most non-attenders (65.5%) and attenders (88.5%) intended to attend next time they were invited for cervical screening, and resistance to mass screening on principle did not seem to have great influence on the number of non-attenders. Both non-attenders and attenders had poor knowledge of the smear test. No significant difference was found concerning the characteristics of the general practice used by non-attenders and attenders. CONCLUSIONS The main barriers to regular cervical screening are insufficient contact with the GP and psychological unpleasantness associated with the gynecological examination. Resistance to cervical screening on principle does not seem to have a great influence on attendance.
Future Generation Computer Systems ( ) – Future Generation Computer Systems a Task-level Adaptive Mapreduce Framework for Real-time Streaming Data in Healthcare Applications

• We propose a task-level adaptive MapReduce framework for healthcare applications. • We prove the optimal runtime Map and Reduce task count when workload changes. • Our method extends the MapReduce programming model to process streaming data. • Our method also includes two methods to predict streaming data workload in run time. • We demonstrate the effectiveness of the method on real-life workload benchmark. Available online xxxx Keywords: Adaptive MapReduce Big data Healthcare scientific applications Kalman filter Parallel processing a b s t r a c t Healthcare scientific applications, such as body area network, require of deploying hundreds of interconnected sensors to monitor the health status of a host. One of the biggest challenges is the streaming data collected by all those sensors, which needs to be processed in real time. Follow-up data analysis would normally involve moving the collected big data to a cloud data center for status reporting and record tracking purpose. Therefore, an efficient cloud platform with very elastic scaling capacity is needed to support such kind of real time streaming data applications. The current cloud platform either lacks of such a module to process streaming data, or scales in regard to coarse-grained compute nodes. In this paper, we propose a task-level adaptive MapReduce framework. This framework extends the generic MapReduce architecture by designing each Map and Reduce task as a consistent running loop daemon. The beauty of this new framework is the scaling capability being designed at the Map and Task level, rather than being scaled from the compute-node level. This strategy is capable of not only scaling up and down in real time, but also leading to effective use of compute resources in cloud data center. As a first step towards implementing this framework in real cloud, we developed a simulator that captures workload strength, and provisions the amount of Map and Reduce tasks just in need and in real time. To further enhance the framework, we applied two streaming data workload prediction methods, smoothing and Kalman filter, to estimate the unknown workload characteristics. We see 63.1% performance improvement by using the Kalman filter method to predict the workload. We also use real streaming data workload trace to test the framework. Experimental results show that this framework schedules the Map and Reduce tasks very efficiently, as the streaming data changes its arrival rate.
Self-Supervised Learning for Time Series: Contrastive or Generative?

Self-supervised learning (SSL) has recently emerged as a powerful approach to learning representations from large-scale unlabeled data, showing promising results in time series analysis. The self-supervised representation learning can be categorized into two mainstream: contrastive and generative. In this paper, we will present a comprehensive comparative study between contrastive and generative methods in time series. We first introduce the basic frameworks for contrastive and generative SSL, respectively, and discuss how to obtain the supervision signal that guides the model optimization. We then implement classical algorithms (SimCLR vs. MAE) for each type and conduct a comparative analysis in fair settings. Our results provide insights into the strengths and weaknesses of each approach and offer practical recommendations for choosing suitable SSL methods. We also discuss the implications of our findings for the broader field of representation learning and propose future research directions. All the code and data are released at \url{https://github.com/DL4mHealth/SSL_Comparison}.