Miracle-dz/UniFAR-FTUs huggingface dataset:
Pix2Repair: Implicit Shape Restoration from Images

We present Pix2Repair, an automated shape repair approach that generates restoration shapes from images to repair fractured objects. Prior repair approaches require a high-resolution watertight 3D mesh of the fractured object as input. Input 3D meshes must be obtained using expensive 3D scanners, and scanned meshes require manual cleanup, limiting accessibility and scalability. Pix2Repair takes an image of the fractured object as input and automatically generates a 3D printable restoration shape. We contribute a novel shape function that deconstructs a latent code representing the fractured object into a complete shape and a break surface. We show restorations for synthetic fractures from the Geometric Breaks and Breaking Bad datasets, and cultural heritage objects from the QP dataset, and for real fractures from the Fantastic Breaks dataset. We overcome challenges in restoring axially symmetric objects by predicting view-centered restorations. Our approach outperforms shape completion approaches adapted for shape repair in terms of chamfer distance, earth mover's distance, normal consistency, and percent restorations generated.
Improving Textless Spoken Language Understanding with Discrete Units as Intermediate Target

Spoken Language Understanding (SLU) is a task that aims to extract semantic information from spoken utterances. Previous research has made progress in end-to-end SLU by using paired speech-text data, such as pre-trained Automatic Speech Recognition (ASR) models or paired text as intermediate targets. However, acquiring paired transcripts is expensive and impractical for unwritten languages. On the other hand, Textless SLU extracts semantic information from speech without utilizing paired transcripts. However, the absence of intermediate targets and training guidance for textless SLU often results in suboptimal performance. In this work, inspired by the content-disentangled discrete units from self-supervised speech models, we proposed to use discrete units as intermediate guidance to improve textless SLU performance. Our method surpasses the baseline method on five SLU benchmark corpora. Additionally, we find that unit guidance facilitates few-shot learning and enhances the model's ability to handle noise.
Using Limited Trial Evidence to Credibly Choose Treatment Dosage when Efficacy and Adverse Effects Weakly Increase with Dose

In medical treatment and elsewhere, it has become standard to base treatment intensity (dosage) on evidence in randomized trials. Yet it has been rare to study how outcomes vary with dosage. In trials to obtain drug approval, the norm has been to specify some dose of a new drug and compare it with an established therapy or placebo. Design-based trial analysis views each trial arm as qualitatively different, but it may be highly credible to assume that efficacy and adverse effects (AEs) weakly increase with dosage. Optimization of patient care requires joint attention to both, as well as to treatment cost. This paper develops methodology to credibly use limited trial evidence to choose dosage when efficacy and AEs weakly increase with dose. I suppose that dosage is an integer choice t in (0, 1, . . . , T), T being a specified maximum dose. I study dosage choice when trial evidence on outcomes is available for only K dose levels, where K<T + 1. Then the population distribution of dose response is partially rather than point identified. The identification region is a convex polygon determined by linear equalities and inequalities. I characterize clinical and public-health decision making using the minimax-regret criterion. A simple analytical solution exists when T = 2 and computation is tractable when T is larger.
Arguments for the physical nature of the triggered ion-acoustic waves observed on the Parker Solar Probe

Triggered ion-acoustic waves are a pair of coupled waves observed in the previously unexplored plasma regime near the Sun. They may be capable of producing important effects on the solar wind. Because this wave mode has not been observed or studied previously and it is not fully understood, the issue of whether it has a natural origin or is an instrumental artifact can be raised. This paper discusses this issue by examining 13 features of the data such as whether the triggered ion-acoustic waves are electrostatic, whether they are both narrow-band, whether they satisfy the requirement that the electric field is parallel to the k-vector, whether the phase difference between the electric field and the density fluctuations is 90 degrees, whether the two waves have the same phase velocity as they must if they are coupled, whether the phase velocity is that of an ion-acoustic wave, whether they are associated with other parameters such as electron heating, whether the electric field instrument otherwise performed as expected, etc. The conclusion reached from these analyses is that triggered ion-acoustic waves are highly likely to have a natural origin although the possibility that they are artifacts unrelated to processes occurring in the natural plasma cannot be eliminated. This inability to absolutely rule out artifacts as the source of a measured result is a characteristic of all measurements.
FineMorphs: Affine-diffeomorphic sequences for regression

A multivariate regression model of affine and diffeomorphic transformation sequences - FineMorphs - is presented. Leveraging concepts from shape analysis, model states are optimally"reshaped"by diffeomorphisms generated by smooth vector fields during learning. Affine transformations and vector fields are optimized within an optimal control setting, and the model can naturally reduce (or increase) dimensionality and adapt to large datasets via suboptimal vector fields. An existence proof of solution and necessary conditions for optimality for the model are derived. Experimental results on real datasets from the UCI repository are presented, with favorable results in comparison with state-of-the-art in the literature and densely-connected neural networks in TensorFlow.
Deep Progressive Feature Aggregation Network for High Dynamic Range Imaging

High dynamic range (HDR) imaging is an important task in image processing that aims to generate well-exposed images in scenes with varying illumination. Although existing multi-exposure fusion methods have achieved impressive results, generating high-quality HDR images in dynamic scenes is still difficult. The primary challenges are ghosting artifacts caused by object motion between low dynamic range images and distorted content in under and overexposed regions. In this paper, we propose a deep progressive feature aggregation network for improving HDR imaging quality in dynamic scenes. To address the issues of object motion, our method implicitly samples high-correspondence features and aggregates them in a coarse-to-fine manner for alignment. In addition, our method adopts a densely connected network structure based on the discrete wavelet transform, which aims to decompose the input features into multiple frequency subbands and adaptively restore corrupted contents. Experiments show that our proposed method can achieve state-of-the-art performance under different scenes, compared to other promising HDR imaging methods. Specifically, the HDR images generated by our method contain cleaner and more detailed content, with fewer distortions, leading to better visual quality.
Efficacy of Naprapathy in Brachial Plexus Injury: Protocol for a Randomized Clinical Trial

Background Clinical rehabilitation for brachial plexus injury is difficult in terms of chronic pain and dysfunction. Physiotherapy is considered a routine intervention for rehabilitation. Common physical therapy may require a variety of instruments. One approach that does not need instruments, but belongs to the field of complementary and alternative medicine, is naprapathy. Naprapathy, also called Tuina in China, has been applied in rehabilitation after brachial plexus injury for a long time. Naprapathy can relieve chronic neuropathic pain, promote local blood circulation, and improve body edema. Naprapathy can passively help improve motor functions in patients with peripheral nerve injury. However, the efficacy of naprapathy in improving rehabilitation after brachial plexus injury is unclear. Objective This study aims to evaluate the additional value of naprapathy when combined with conventional physical therapy for the treatment of brachial plexus injury. Methods This will be a single-center randomized controlled trial. A total of 116 eligible patients with brachial plexus injury will be randomly divided into an experimental group (naprapathy plus physical therapy group) or a control group (physical therapy group). The participants will be followed up for 4 weeks of treatment. Observation outcomes will include the visual analog scale score, upper limb index, electromyography findings, and adverse reactions, among others. The measuring points for outcomes will be the baseline and the completion of treatment. In addition, a quality control group independent from the research team will be set up to control the quality of the trial. Finally, the data will be analyzed using SPSS software (version 21.0; IBM Corp). Results The study is recruiting participants. The first participant was enrolled in September 2021. As of January 2023, a total of 100 participants have been enrolled. The trial is expected to be completed by September 2023. The study protocol was approved by the Ethics Review Committee of Yue Yang Hospital affiliated with the Shanghai University of Traditional Chinese Medicine (2021-012). Conclusions One limitation of this trial is that we will be unable to achieve strict double-blinding because of the features of naprapathy. The trial aims to contribute reliable evidence for decision-making in naprapathy for treating brachial plexus injury. Trial Registration Chinese Clinical Trial Registry ChiCTR2100043515; http://www.chictr. org.cn/showproj.aspx? proj=122154 International Registered Report Identifier (IRRID) DERR1-10.2196/46054
Neutrophil extracellular trap is an important connection between hemodialysis and acute myocardial infarction

Abstract The incidence of acute myocardial infarction (AMI) in hemodialysis (HD) patients is high and the prognosis is extremely poor. However, the potential connection between HD and AMI, and its regulatory mechanisms remain unclear. In this study, the gene expression profiles of HD (GSE15072) and AMI (GSE66360) were downloaded from the Gene Expression Omnibus database, common differentially expressed genes (DEGs) were obtained using the limma R package, the biological functions were analyzed according to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, machine learning was conducted to identify hub genes. Receiver operating characteristic curves and gene set enrichment analyses were used to explore the characters and biological function of hub genes, networks were used for candidate identification of transcription factor (TF), microRNA (miRNA), and drug. After a total of 255 common DEGs were selected, GO and KEGG analyses indicated that neutrophil extracellular trap (NET) may be a potential connection between HD and AMI, LILRB2, S100A12, CYBB, ITGAM, and PPIF were finally identified as hub genes. The area under curve of LILRB2, S100A12, and PPIF was higher than 0.8 in both datasets. Networks show the relationship between hub genes, TF, and miRNA, also the relationship between potential drugs and protein. In conclusion, NETs may be the potential connection between AMI and HD. The potential hub gene, signaling pathways, and drugs provided by this study may contribute to future AMI prevention and intervention in HD patients.
A generalization of wave-equation migration velocity analysis

Wave-equation migration velocity analysis is derived from wavefield-continuation migration techniques. The velocity model is updated by optimizing certain properties of the migrated images. Different migration velocity analysis optimization criteria exist, of which two commonly used are fitting a target image and minimizing the differential semblance of migrated images. Both techniques are special cases of a general family of optimization functions. Fitting a target image is an attractive technique because we can guide the solution in the desired direction. However, we can only progress in small steps with the target image being kept within the Born approximation with respect to the reference image. Minimizing differential semblance is an attractive technique, too, because we are operating with small differences of nearby offsets which are likely within the Born approximation. However, this method is not directly guided toward the solution and aliasing or any remnants of coherent noise, like multiples or converted waves, can cause it to diverge.
Estimating the Integrated Parameter of the Time-Varying Parameter Self-Exciting Process

We introduce and show the existence of a continuous time-varying parameter extension model to the self-exciting point process. The kernel shape is assumed to be exponentially decreasing. The quantity of interest is defined as the integrated parameter over time $T^{-1} \int_0^T \theta_t^* dt$, where $\theta_t^*$ is the time-varying parameter. To estimate it na\"{i}vely, we chop the data into several blocks, compute the maximum likelihood estimator (MLE) on each block, and take the average of the local estimates. Correspondingly, we give conditions on the parameter process and the block length under which we can establish the local central limit theorem, and the boundedness of moments of order $2\kappa$ of the local estimators, where $\kappa > 1$. Under those assumptions, the global estimator asymptotic bias explodes asymptotically. As a consequence, we provide a non-na\"{i}ve estimator, which is constructed as the na\"{i}ve one when applying a first-order bias reduction to the local MLE. We derive such first-order bias formula for the self-exciting process, and provide further conditions under which the non-na\"{i}ve global estimator is asymptotically unbiased. Finally, we obtain the associated global central limit theorem.
Longitudinal change of circulating tumor cell level and its relationship with immune checkpoint inhibitor-based treatment benefits in unresectable, metastatic colorectal cancer patients

Abstract Objective Circulating tumor cell (CTC) exerts diagnostic and prognostic value in colorectal cancer (CRC) patients. This study intended to further investigate the longitudinal change of CTC count, and its correlation with the prognosis of immune checkpoint inhibitor (ICI)-based treatments in unresectable, metastatic CRC patients. Methods Fifty-six unresectable, metastatic CRC patients receiving ICI-based treatments were enrolled. CTC count was assessed by the CellSearch system at baseline and month (M)2 in their peripheral blood samples. Results Forty-one (73.2%) and sixteen (28.5%) patients had CTC count ≥1 and ≥5 at baseline, respectively. Meanwhile, CTC count at M2 was decreased versus that at baseline (median (interquartile range): 1.0 (0.0–3.0) versus 3.0 (0.0–5.0)) (p < 0.001). Besides, increased CTC count at baseline (p = 0.009) and M2 (p = 0.006) associated with a reduced overall response rate. Baseline CTC count ≥5 related to worse progression-free survival (PFS) (p = 0.007), but baseline CTC count ≥1 did not; additionally, baseline CTC count ≥1 (p = 0.043) and ≥5 (p = 0.016) linked to shorter overall survival (OS). Furthermore, M2 CTC count ≥1 (p = 0.002) and ≥5 (p < 0.001) both correlated with poor PFS; meanwhile, M2 CTC count ≥1 (p = 0.006) and ≥5 (p < 0.001) also related to worse OS. After adjustment, only CTC count at M2 ≥ 5 independently associated with unsatisfactory PFS (hazard ratio (HR)=3.218, p = 0.011) and OS (HR = 3.229, p = 0.038). Conclusions CTC count is decreased during ICI-based treatments, its reduction represents satisfactory treatment outcomes in unresectable, metastatic CRC patients. Notably, the CTC count at 5 as a cutting threshold after a two-month treatment has an impressive prognostic value.
Unusual relapse of low hypodiploid acute lymphoblastic leukaemia in a family with Li‐Fraumeni syndrome

To the Editor: In 2007, a 7-year-old female from a family with Li–Fraumeni syndrome (LFS) was reviewed with hip and back pain, weight loss, fever, a wide-based gait and decreased left leg sensation in the L4 region. Full blood count results demonstrated haemoglobin 90 g/L, platelets 261 × 109/L and white cell count (WCC) 3.6 × 109/L. The blood film showed a leukoerythroblastic picture without circulating blast cell population. Magnetic resonance imaging demonstrated signal change throughout the lumbar spine, more pronounced around L3 (Figure S1). In view of the family history, the differential diagnosis was wide. Bone marrow aspirate was unsuitable for flow cytometry, but showed primitive cells suspicious of non-haemopoietic tumour. The diagnosis of CD10 B precursor acute lymphoblastic leukaemia (ALL) was established by bone marrow trephine analysis with immunohistochemistry (Figure S2). Restricted cytogenetic analyses showed 46,XX[14] by G-banding with fluorescent in situ hybridisation (FISH) demonstrating loss of FOXO1/13q14.11 [44%], gain of MYC/8q24.21 [9%] and gain of RUNX1/21q22.12 [21%]. The patient was treated according to regimen A (UKALL2003) and achieved remission after three-drug induction.1 She received intensification/central nervous system-directed phase (intrathecal methotrexate), interim maintenance, two delayed intensification blocks and completed treatment in 2009. She presented with hypercalcaemia 7 years later. Investigations confirmed a diagnosis of ALL. Although the phenotype resembled the profile of the first presentation of leukaemia (Table S1), the genetic aberrations appeared incongruent. It was pivotal to establish whether this was a second primary or relapsed ALL in the context of genetic predisposition. G-banding revealed low hypodiploidy (36,XX,−2,−3,−4, del(5)(q31q35),−7,−12,−13,−14,−15,−16,−17[13]/46,XX[7]. The karyotype showed a typical aneuploidy pattern with monosomy 3, 7, 15, 16, 17 and disomy 1, 6, 11 and 18.2 Genome-wide copy number analysis mirrored the karyotype described above (Figures S3 and S4). Using the karyotype established at relapse, targeted interphase FISH was undertaken in archival diagnostic material, which showed (i) monosomy 15,monosomy 17 pattern [41/100], (ii) monosomy 3, disomy 8 [39/100] and disomy 3, tetrasomy 8 [9/100], and (iii) monosomy 12, disomy 21 [13/31], disomy 12, tetrasomy 21 [4/31] (Figure 1). These comprehensive FISH analyses showed clear evidence that the relapse low hypodiploid clone was present at diagnosis in approximately 40%of cells. At diagnosis, a proportion of the hypodiploid clone F IGURE 1 Fluorescence in situ hybridisation (FISH) analysis of acute lymphoblastic leukaemia (ALL) at initial presentation with probes complementary toMYC (8q24, red) and BCL6 (3q27, green). The hypodiploid clone characterised bymonosomy 3 and disomy 8 is indicated with red circles. Themasked or doubled-up hypodiploid clone, indicatedwith purple rings, demonstrated disomy 3 and tetrasomy 8. Normal cells are not marked.
F11R/JAM-A: why do platelets express a molecule which is also present in tight junctions?

Abstract F11 receptor (F11R)/Junctional Adhesion Molecule –A (JAM-A) is a transmembrane protein which belongs to the immunoglobulin superfamily of cell adhesion molecules. F11R/JAM-A is present in epithelial cells, endothelial cells, leukocytes, and blood platelets. In epithelial and endothelial cells, it takes part in the formation of tight junctions. In these structures, molecules of F11R/JAM-A located on adjacent cells form homodimers and thus take part in stabilization of cellular layer integrity. In leukocytes, F11R/JAM-A was shown to play role in their transmigration through the vascular wall. Paradoxically, the function of F11R/JAM-A in blood platelets, where it was primarily discovered, is much less understood. It has been proven to regulate downstream signaling of αIIbβ3 integrin and to mediate platelet adhesion under static conditions. It was also shown to contribute to transient interactions of platelets with inflamed vascular wall. The review is aimed at summarizing the current state of knowledge of the platelet pool of F11R/JAM-A. The article also presents perspectives of the future research to better understand the role of this protein in hemostasis, thrombosis, and other processes where blood platelets are involved. Plain Language Summary The molecule of a complex name F11R/JAM-A is a protein which was primarily discovered on blood platelets. Later, the presence of the same molecule was confirmed on endothelial cells and epithelial cells. From the moment of the discovery, most of the research was focused on the role of this protein in the latter types of cells. It was found to be an important element of so-called tight junctions. These structures are crucial for maintaining of integrity and selective permeability of cellular layers composed of these types of cells. In the following years, the presence of F11R/JAM-A has also been reported on leukocytes. An important role of specific type of leukocytes is their penetration to the sites of inflammation. Interplay of F11R/JAM-A present on endothelium and that on leukocyte is involved in this process. But what about the role of this protein in blood platelets where it was originally discovered? There is limited knowledge regarding this issue. It was found to play a role in the ability of platelets to adhere to a surface under static conditions, but it is not known if the same is true under flow. Is the protein necessary for platelets to aggregate and form thrombus? Genetically engineered mice were created which lack this protein in blood platelets to answer this question. These platelets were abnormally reactive, as it transpired that the protein plays a role of a negative regulator to one of the most important mechanisms, which triggers platelet aggregation. But is this inhibitory function the only task F11R/JAM-A has to fulfil in platelets? Presented review collects all the knowledge regarding this protein in blood platelets and tries to show interesting routes which need exploration.
Current Open Trials and Molecular Update for Pediatric Embryonal Tumors

Background: Embryonal tumors are highly malignant cancers of the central nervous system, with a relatively high incidence in infants and young children. Even with intensive multimodal treatment, the prognosis of many types is guarded, and treatment-related toxicity is significant. Recent advances in molecular diagnostics allowed the discovery of novel entities and inter-tumor subgroups, with opportunities for improved risk-stratification and treatment approaches. Summary: Medulloblastomas separate into four distinct subgroups with distinct clinicopathologic characteristics, and data from recent clinical trials for newly diagnosed medulloblastoma support subgroup-specific treatment approaches. Atypical teratoid rhabdoid tumor (ATRT), embryonal tumor with multilayered rosettes (ETMR), and pineoblastoma, as well as other rare embryonal tumors, can be distinguished from histologically similar tumors by virtue of characteristic molecular findings, with DNA methylation analysis providing a strong adjunct in indeterminate cases. Methylation analysis can also allow further subgrouping of ATRT and pineoblastoma. Despite the dire need to improve outcomes for patients with these tumors, their rarity and lack of actionable targets lead to a paucity of clinical trials and novel therapeutics. Key Messages: (1) Embryonal tumors can be accurately diagnosed with pediatric-specific sequencing techniques. (2) Medulloblastoma risk stratification and treatment decisions should take into account molecular subgroups. (3) There is a dire need for a novel collaborative clinical trial design to improve outcomes is rare pediatric embryonal tumors.