CofiFab: Coarse-to-fine fabrication of large 3D objects

This paper presents CofiFab, a coarse-to-fine 3D fabrication solution, which combines 3D printing and 2D laser cutting for cost-effective fabrication of large objects at lower cost and higher speed. Our key approach is to first build coarse internal base structures within the given 3D object using laser-cutting, and then attach thin 3D-printed parts, as an external shell, onto the base to recover the fine surface details. CofiFab achieves this with three novel algorithmic components. First, we formulate an optimization model to compute fabricatable polyhedrons of maximized volume, as the geometry of the internal base. Second, we devise a new interlocking scheme to tightly connect laser-cut parts into a strong internal base, by iteratively building a network of nonorthogonal interlocking joints and locking parts around polyhedral corners. Lastly, we also optimize the partitioning of the external object shell into 3D-printable parts, while saving support material and avoiding overhangs. These components also consider aesthetics, stability and balancing in addition to cost saving. As a result, CofiFab can efficiently produce large objects by assembly. To evaluate its effectiveness, we fabricate objects of varying shapes and sizes, where CofiFab significantly improves compared to previous methods

CP-EB: Talking Face Generation with Controllable Pose and Eye Blinking Embedding

This paper proposes a talking face generation method named "CP-EB" that takes an audio signal as input and a person image as reference, to synthesize a photo-realistic people talking video with head poses controlled by a short video clip and proper eye blinking embedding. It's noted that not only the head pose but also eye blinking are both important aspects for deep fake detection. The implicit control of poses by video has already achieved by the state-of-art work. According to recent research, eye blinking has weak correlation with input audio which means eye blinks extraction from audio and generation are possible. Hence, we propose a GAN-based architecture to extract eye blink feature from input audio and reference video respectively and employ contrastive training between them, then embed it into the concatenated features of identity and poses to generate talking face images. Experimental results show that the proposed method can generate photo-realistic talking face with synchronous lips motions, natural head poses and blinking eyes.Comment: Accepted by the 21st IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA 2023

A Transformer-Based Model for Effective Representation of Geospatial Data and Context

Machine learning (ML) and Artificial Intelligence (AI) models have been increasingly adopted for geospatial tasks. However, geospatial data (such as points and raster cells) are often influenced by underlying spatial effects, and current model designs often lack adequate consideration of these effects. Determining the efficient model structure for representing geospatial data and capturing the underlying complex spatial and contextual effects still needs to be explored. To address this gap, we propose a Transformer-like encoder-decoder architecture to first represent geospatial data with respect to their corresponding geospatial context, and then decode the representation for task-specific inferences. The encoder consists of embedding layers that transform the input location and attributes of geospatial data into meaningful embedding vectors. The decoder comprises task-specific neural network layers that map the encoder outputs to the final output. Spatial contextual effects are measured using explainable artificial intelligence (XAI) methods. We evaluate and compare the performance of our model with other model structures on both synthetic and real-world datasets for spatial regression and interpolation tasks. This work proposes a generalizable approach to better modeling and measuring complex spatial contextual effects, potentially contribute to efficient and reliable urban analytic applications that require geo-context information

Masonry shell structures with discrete equivalence classes

This paper proposes a method to model masonry shell structures where the shell elements fall into a set of discrete equivalence classes. Such shell structure can reduce the fabrication cost and simplify the physical construction due to reuse of a few template shell elements. Given a freeform surface, our goal is to generate a small set of template shell elements that can be reused to produce a seamless and buildable structure that closely resembles the surface. The major technical challenge in this process is balancing the desire for high reusability of template elements with the need for a seamless and buildable final structure. To address the challenge, we define three error metrics to measure the seamlessness and buildability of shell structures made from discrete equivalence classes and develop a hierarchical cluster-and-optimize approach to generate a small set of template elements that produce a structure closely approximating the surface with low error metrics. We demonstrate the feasibility of our approach on various freeform surfaces and geometric patterns, and validate buildability of our results with four physical prototypes. Code and data of this paper are at https://github.com/Linsanity81/TileableShell

Correlation of lifestyle behaviors during pregnancy with postpartum depression status of puerpera in the rural areas of South China

BackgroundPostpartum depression (PPD) is among the most common postpartum complications. Its prevalence is associated with strong regional variability. Women in rural areas of China have a high risk of PPD. The aim of this study was to investigate the PPD status of women in rural South China and explore the effects of modifiable lifestyle behaviors during pregnancy on their PPD status, thereby providing a scientific basis for the prevention and intervention of PPD in rural China.MethodsA cohort study was conducted on 261 women from four maternal health institutions situated in rural areas of Guangdong Province and the Guangxi Zhuang Autonomous Region from October 2021 to December 2022. The questionnaires were administered to these women to obtain data about sociodemographic characteristics, health literacy, physical activity during pregnancy, and sleep and dietary status during pregnancy, as well as depression status on the 42nd day after delivery. The lifestyle behaviors during pregnancy and the PPD status of the study population were analyzed. Multiple linear regression models were used to determine the correlation between lifestyle behaviors and PPD status. Path analysis was performed to explore the interaction between various lifestyle behaviors.ResultsA total of 14.6% of women had a PPD status. Women who continued to work during pregnancy had an Edinburgh Postpartum Depression Scale (EPDS) score of 1.386 points higher than that of women who did not (В = 1.386, β = 0.141, p = 0.029). For every 1-point increase in the infant feeding-related knowledge score and pregnancy diet diversity score, the EPDS score decreased by 0.188 and 0.484 points, respectively, and for every 1-point increase in the Pittsburgh sleep quality index score, the EPDS score increased by 0.288 points. Age was related to infant feeding-related knowledge (indirect path coefficient = 0.023). During pregnancy, sedentary time was correlated with sleep quality (indirect path coefficient = 0.031) and employment status (indirect path coefficient = 0.043).ConclusionEmployment status, infant feeding-related knowledge, sleep quality, and diet diversity during pregnancy directly influenced the PPD status, while age and sedentary time during pregnancy indirectly influenced the PPD status. Promoting healthy lifestyle behaviors, including reducing sedentary time, improving sleep quality, and increasing dietary diversity, may be effective in reducing PPD occurrence

Cost-effectiveness of neoadjuvant pembrolizumab plus chemotherapy with adjuvant pembrolizumab for early-stage non-small cell lung cancer in the United States

IntroductionPerioperative (neoadjuvant and adjuvant) pembrolizumab has shown favorable efficacy in patients with early-stage non-small cell lung cancer (NSCLC). This study aims to evaluate the cost-effectiveness of this treatment from the perspective of the United States healthcare payers.MethodsWe established a Markov model to compare the cost-effectiveness of perioperative pembrolizumab with that of neoadjuvant chemotherapy in 21-day cycles, utilizing data from the phase 3 KEYNOTE-671 trial. Additional data were extracted from other publications or online sources. Sensitivity analyses were conducted to evaluate the robustness of the findings. A willingness-to-pay threshold of $150,000 per quality-adjusted life-years (QALYs) gained was established. The main outcomes of this study were the measurement of QALYs, overall costs, incremental cost-effectiveness ratio (ICER), and net monetary benefit (NMB).ResultsDuring a 10-year time horizon, the total costs of perioperative pembrolizumab and the control treatment were$224,779.1 and $110,026.3, respectively. The QALYs were 4.19 and 2.97 for the two treatments, respectively, which led to an ICER of$94,222.29 per QALY gained. The NMB at the WTP threshold at $150,000 per QALY gained was$67,931.3. One-way sensitivity analysis identified the cost of pembrolizumab as the primary factor influencing cost-effectiveness. Probabilistic sensitivity analysis indicated a 97.7% probability of perioperative pembrolizumab being cost-effective at the WTP threshold.ConclusionsFrom the perspective of the United States healthcare payers, perioperative pembrolizumab is a cost-effective treatment for patients with early-stage NSCLC

Extracellular histones cause intestinal epithelium injury and disrupt its barrier function in vitro and in vivo.

Extracellular histones are cytotoxic to various cells and have been extensively proven a vital mediator of multiple organ injuries. However, the effect of extracellular histones on the intestine remains largely unknown. This study aimed to clarify the effect of extracellular histones on the intestine. IEC-6, a cell line of rat small intestinal epithelial crypt, and C57BL/6 or ICR mice were treated with histones. The IEC-6 cells treated with histones from 20 μg/mL to 200 μg/mL for 0-24 h displayed a decline of cell viability and an increase of cell death in a concentration- and time-dependent manner. Moreover, histones (100 μg/mL) induced IEC-6 apoptosis through activating caspase 3 and necroptosis through up-regulation of receptor-interacting serine/threonine protein kinase 1 and 3 (RIPK1 and RIPK3), phosphorylated mixed-lineage kinase domain-like protein (p-MLKL) along with the decrease of caspase-8. Histones treatment disturbed zonular occludens 1 (ZO-1) expression and increased permeability of IEC-6 cell monolayer. In vivo, histones 50 mg/kg injection caused mice intestinal edema, loss apex of villus, epithelial lifting down the sides of the villi, and increased neutrophil infiltration. Elevation of serum intestinal fatty acid binding protein (I-FABP), d-lactate, or Diamine oxidase (DAO) and loss of tight junction protein, ZO-1, at 3 h and 6 h after histones injection strongly indicated severe intestinal epithelium injury, which led to increased permeability of the intestine. In conclusion, extracellular histones cause intestinal epithelial damage via direct cytotoxicity. Consequently, intestinal epithelial tight junction and barrier integrity are disrupted, which may play pivotal roles in diverse diseases

Hemoconcentration is associated with early faster fluid rate and increased risk of persistent organ failure in acute pancreatitis patients.

Background:Controversies existed surrounding the use of hematocrit to guide early fluid therapy in acute pancreatitis (AP). The association between hematocrit, early fluid therapy, and clinical outcomes in ward AP patients needs to be investigated. Methods:Data from prospectively maintained AP database and retrospectively collected details of fluid therapy were analyzed. Patients were stratified into three groups: Group 1, hematocrit 44% at 24 h; Group 3: hematocrit >44% on admission and decreased thereafter during first 24 h. "Early" means first 24 h after admission. Baseline characteristics, early fluid rates, and clinical outcomes of the three groups were compared. Results:Among the 628 patients, Group 3 had a higher hematocrit level, greater baseline predicted severity, faster fluid rate, and more fluid volume in the first 24 h compared with Group 1 or 2. Group 3 had an increased risk for persistent organ failure (POF; odds ratio 2, 95% confidence interval [1.1-3.8], P = 0.03) compared with Group 1 after adjusting for difference in baseline clinical severity scores, there was no difference between Group 2 and Group 3 or Group 1. Multivariate regression analyses revealed that hemoconcentration and early faster fluid rate were risk factors for POF and mortality (both P < 0.05). Conclusions:Hemoconcentration is associated with faster fluid rate and POF in ward AP patients. Randomized trials comparing standardized early fast and slow fluid management is warranted

Shared genetics and causal relationships between major depressive disorder and COVID-19 related traits: a large-scale genome-wide cross-trait meta-analysis

IntroductionThe comorbidity between major depressive disorder (MDD) and coronavirus disease of 2019 (COVID-19) related traits have long been identified in clinical settings, but their shared genetic foundation and causal relationships are unknown. Here, we investigated the genetic mechanisms behind COVID-19 related traits and MDD using the cross-trait meta-analysis, and evaluated the underlying causal relationships between MDD and 3 different COVID-19 outcomes (severe COVID-19, hospitalized COVID-19, and COVID-19 infection).MethodsIn this study, we conducted a comprehensive analysis using the most up-to-date and publicly available GWAS summary statistics to explore shared genetic etiology and the causality between MDD and COVID-19 outcomes. We first used genome-wide cross-trait meta-analysis to identify the pleiotropic genomic SNPs and the genes shared by MDD and COVID-19 outcomes, and then explore the potential bidirectional causal relationships between MDD and COVID-19 outcomes by implementing a bidirectional MR study design. We further conducted functional annotations analyses to obtain biological insight for shared genes from the results of cross-trait meta-analysis.ResultsWe have identified 71 SNPs located on 25 different genes are shared between MDD and COVID-19 outcomes. We have also found that genetic liability to MDD is a causal factor for COVID-19 outcomes. In particular, we found that MDD has causal effect on severe COVID-19 (OR = 1.832, 95% CI = 1.037–3.236) and hospitalized COVID-19 (OR = 1.412, 95% CI = 1.021–1.953). Functional analysis suggested that the shared genes are enriched in Cushing syndrome, neuroactive ligand-receptor interaction.DiscussionOur findings provide convincing evidence on shared genetic etiology and causal relationships between MDD and COVID-19 outcomes, which is crucial to prevention, and therapeutic treatment of MDD and COVID-19