CAM Model Research Articles

Towards a Generalized Bayesian Model of Reconstructive Memory

AbstractPrior knowledge has long been known to shape reconstruction from memory. An individual stimulus from a category is often remembered to be closer to the center of that category than its true location. This effect, together with more complex memory effects that involve prior knowledge at multiple levels of abstraction, has been successfully explained by the Category Adjustment Model (CAM; Huttenlocher et al. Journal of Experimental Psychology: General, 129(2), 220, 2000) and its extensions. However, recent experimental results diverge from CAM’s predictions showing that reconstructive memory for atypical category examples is influenced by the category center less than that of typical category examples. To unify these findings, we propose a generalized Bayesian model of reconstructive memory, called the generalized CAM model (g-CAM). We demonstrate through simulations that g-CAM can account for previously known effects of reconstructive memory, while additionally capturing recent empirical findings involving atypical category examples.

Combination of JAKi and HDACi Exerts Antiangiogenic Potential in Cutaneous T-Cell Lymphoma.

Angiogenesis plays a pivotal role in the growth and metastasis of tumors, including the development and progression of cutaneous lymphomas. The chick embryo CAM model has been utilized in various studies to assess the growth rate, angiogenic potential, and metastatic capability of different tumor types and malignant cell lines. However, the precise mechanisms of angiogenesis in CTCL and the influence of Ruxolitinib or Resminostat on angiogenesis in hematological malignancies and solid tumors are not well understood. Recent in vitro and in vivo data have demonstrated the synergistic inhibition of tumorigenesis and metastasis in experimental models of CTCL when using the combination of Resminostat (HDACi) with Ruxolitinib (JAKi). The present work aims to elucidate the effects of this combination on the tumor microenvironment's vascular components. We investigated the effects of Ruxolitinib (JAKi) in combination with Resminostat (HDACi) treatment in transendothelial migration of CTCL cells (106 MyLa and SeAx) by using a transwell-based transendothelial migration assay and tumor angiogenesis in vivo. We used the CTCL chick embryo CAM model with xenografted tumors derived from implanted MyLa and SeAx cells and administered topically 15 μM ruxolitinib and 5 μM Resminostat every two days during a 5-day period. JAKi and HDACi inhibited CTCL cell transendothelial migration by 75% and 82% (p < 0.05) in both CTCL engrafted cells (MyLa and SeAx, respectively) compared to the untreated group. Moreover, the combination of ruxolitinib with resminostat blocked angiogenesis by significantly reducing the number of blood vessel formation by 49% and 34% in both MyLa and SeAx, respectively (p < 0.05), indicating that the proposed combination exerted significant anti-angiogenic effects in the CAM CTCL model. Overall, these data provide valuable insights into potential therapeutic strategies targeting angiogenesis in CTCL, paving the way for more effective treatment approaches in the future.

Mathematical Model of the Electronic Cam in Terms of Application in a Dosing Machine

The article analyses the use of servomotors in the control systems of industrial equipment, focusing on the alternative offered by position and speed synchronization in relation to classical mechanical mechanisms. A complete methodology is presented to determine the dynamic parameters of the adopted kinematic system using electronic motion profiles. The results obtained constitute a mathematical model of the execution chain and an analysis of the basic quantities for linear motion, supported by actual measurements of the drive parameters. The merit of the article is to show that the servomotors can significantly simplify the design of the device, make it more flexible in adaptation to different assortments, and allow integration with systems predicting the technical condition of the device. The analysis of the results revealed significant differences in the constant rotational speed of the servomotor, which do not align with previous findings. The results suggest that changing the angular working range of the assembly to the range (205°;270°) could significantly affect the generated linear acceleration, reducing the risk of stalling. The calculations and graphs conducted allowed for the accurate representation of the actual mechanical system, considering its dynamic characteristics. The key conclusion is that precise mathematical modelling is essential to ensure the stability and durability of engineering components.

From crude oil to bitumen: Genetic variability in chemistry and its influence on viscoelastic of binders

The chemical composition and properties of bitumen are derived from crude oil, which directly influences its viscoelastic properties. Six different crude oil sources were examined to explore how crude oil characteristics impact bitumen. The bitumen was produced through in-house atmospheric decompression distillation, and aging tests were conducted on these samples. The chemical properties of the crude oils, virgin binders, and aged binders were analyzed using Fourier Transform Infrared Spectroscopy (FTIR). Additionally, the separation and quantitative analysis of saturates, aromatics, resins, and asphaltenes (SARA) in crude oil and bitumen binders were carried out using Thin Layer Chromatography-Flame Ionization Detector (TLC-FID). Sweep tests on binders were conducted using a Dynamic Shear Rheometer (DSR). Master curves were created based on the CAM model and the 2S2P1D model to assess the dynamic viscoelastic properties of bitumen. The grey correlation method was employed to examine how bitumen chemical composition and properties affect its viscoelasticity. Results indicated that crude oil profoundly influences bitumen's chemical composition and properties. The functional group index and component content of bitumen are inherited from crude oil and are closely linked to the corresponding indices of crude oil. The functional group index, SARA, and colloidal stability coefficients of bitumen are intimately connected to the viscoelastic parameters of bitumen. The impact of the functional group index on the viscoelastic parameters is more pronounced than that of SARA content. This insight is crucial for guiding the selection of oil sources in bitumen production processes.

Porous calcium silicate bioactive material-alginate composite for bone regeneration.

Bone tissue engineering aims to address bone-related problems that arise from trauma, infection, tumors, and surgery. Polymer and calcium silicate bioactive material (BM) based composites are commonly preferred as potential materials for bone treatment. However, the polymer has low bioactivity, thus, the current work aims to prepare a composite scaffold based on BM-sodium alginate (Alg) by varying the Alg percentage to optimize the porous nature of the composite. Primarily, the BM was synthesized by a simple precipitation method using rice husk and eggshell as the precursors of silica and calcium, while the BM-Alg composite was prepared by a facile cross-linking approach. The BM-Alg composite was studied using XRD, FTIR, SEM, and BET techniques. Further, an in vitro bioactivity study was performed in simulated body fluid (SBF) which shows hydroxyapatite formation. The in vitro haemolysis study displayed less than 5% haemolysis. Subsequently, the angiogenesis study was carried out using the ex ovo CAM model which reveals enhanced neovascularization. The MG-63 cells were used to study the biocompatibility, and they displayed a non-toxic nature at a concentration of 10 mg mL-1. Further, the in vivo biocompatibility results also reveal its non-toxic nature. Thus, the BM-Alg composite acts as a potential biocompatible material for bone tissue engineering applications.

Very fast, high-resolution aggregation 3D detection CAM to quickly and accurately find facial fracture areas

Background and objective:The incidence of facial fractures is on the rise globally, yet limited studies are addressing the diverse forms of facial fractures present in 3D images. In particular, due to the nature of the facial fracture, the direction in which the bone fractures vary, and there is no clear outline, it is difficult to determine the exact location of the fracture in 2D images. Thus, 3D image analysis is required to find the exact fracture area, but it needs heavy computational complexity and expensive pixel-wise labeling for supervised learning. In this study, we tackle the problem of reducing the computational burden and increasing the accuracy of fracture localization by using a weakly-supervised object localization without pixel-wise labeling in a 3D image space. Methods:We propose a Very Fast, High-Resolution Aggregation 3D Detection CAM (VFHA-CAM) model, which can detect various facial fractures. To better detect tiny fractures, our model uses high-resolution feature maps and employs Ablation CAM to find an exact fracture location without pixel-wise labeling, where we use a rough fracture image detected with 3D box-wise labeling. To this end, we extract important features and use only essential features to reduce the computational complexity in 3D image space. Results:Experimental findings demonstrate that VFHA-CAM surpasses state-of-the-art 2D detection methods by up to 20% in sensitivity/person and specificity/person, achieving sensitivity/person and specificity/person scores of 87% and 85%, respectively. In addition, Our VFHA-CAM reduces location analysis time to 76 s without performance degradation compared to a simple Ablation CAM method that takes more than 20 min. Conclusion:This study introduces a novel weakly-supervised object localization approach for bone fracture detection in 3D facial images. The proposed method employs a 3D detection model, which helps detect various forms of facial bone fractures accurately. The CAM algorithm adopted for fracture area segmentation within a 3D fracture detection box is key in quickly informing medical staff of the exact location of a facial bone fracture in a weakly-supervised object localization. In addition, we provide 3D visualization so that even non-experts unfamiliar with 3D CT images can identify the fracture status and location.

The immunomodulatory ballet of tumour-derived extracellular vesicles and neutrophils orchestrating the dynamic CD73/PD-L1 pathway in cancer.

Head and neck squamous cell carcinoma (HNSCC) is a global cancer burden with a 5-year overall survival rate of around 50%, stagnant for decades. A tumour-induced immunosuppressive microenvironment contributes to HNSCC progression, with the adenosine (ADO) pathway and an upregulated expression of inhibitory immune checkpoint regulators playing a key role in this context. The correlation between high neutrophil-to-lymphocyte ratio (NLR) with advanced tumour staging suggests involvement of neutrophils (NØ) in cancer progression. Interestingly, we associated a high NLR with an increased intracellular PD-L1 localization in primary HNSCC samples, potentially mediating more aggressive tumour characteristics and therefore synergistically favouring tumour progression. Still, further research is needed to harness this knowledge for effective treatments and overcome resistance. Since it is hypothesized that the tumour microenvironment (TME) may be influenced by small extracellular vesicles (sEVs) secreted by tumours (TEX), this study aims to investigate the impact of HNSCC-derived TEX on NØ and blockade of ADO receptors as a potential strategy to reverse the pro-tumour phenotype of NØ. UMSCC47-TEX exhibited CD73 enzymatic activity involved in ADO signalling, as well as the immune checkpoint inhibitor PD-L1. Data revealed that TEX induce chemotaxis of NØ and the sustained interaction promotes a shift into a pro-tumour phenotype, dependent on ADO receptors (P1R), increasing CD170high subpopulation, CD73 and PD-L1 expression, followed by an immunosuppressive secretome. Blocking A3R reduced CD73 and PD-L1 expression. Co-culture experiments with HNSCC cells demonstrated that TEX-modulated NØ increase the CD73/PD-L1 axis, through Cyclin D-CDK4/6 signalling. To support these findings, the CAM model with primary tumour was treated with NØ supernatant. Moreover, these NØ promoted an increase in migration, invasion, and reduced cell death. Targeting P1R on NØ, particularly A3R, exhibited potential therapeutic strategy to counteract immunosuppression in HNSCC. Understanding the TEX-mediated crosstalk between tumours and NØ offers insights into immunomodulation for improving cancer therapies.

Anti-angiogenic Potential of Trans-chalcone in an In Vivo Chick Chorioallantoic Membrane Model: An ATP Antagonist to VEGFR with Predicted Blood-brain Barrier Permeability.

Glioblastoma multiforme (GBM) is characterized by massive tumorinduced angiogenesis aiding tumorigenesis. Vascular endothelial growth factor A (VEGF-A) via VEGF receptor 2 (VEGFR-2) constitutes majorly to drive this process. Putting a halt to tumordriven angiogenesis is a major clinical challenge, and the blood-brain barrier (BBB) is the prime bottleneck in GBM treatment. Several phytochemicals show promising antiangiogenic activity across different models, but their ability to cross BBB remains unexplored. We screened over 99 phytochemicals having anti-angiogenic properties reported in the literature and evaluated them for their BBB permeability, molecular interaction with VEGFR-2 domains, ECD2-3 (extracellular domains 2-3) and TKD (tyrosine kinase domain) at VEGF-A and ATP binding site, cell membrane permeability, and hepatotoxicity using in silico tools. Furthermore, the anti-angiogenic activity of predicted lead Trans-Chalcone (TC) was evaluated in the chick chorioallantoic membrane. Out of 99 phytochemicals, 35 showed an efficient ability to cross BBB with a probability score of > 0.8. Docking studies revealed 30 phytochemicals crossing benchmark binding affinity < -6.4 kcal/mol of TKD with the native ligand ATP alone. Out of 30 phytochemicals, 12 showed moderate to low hepatotoxicity, and 5 showed a violation of Lipinski's rule of five. Our in silico analysis predicted TC as a BBB permeable anti-angiogenic compound for use in GBM therapy. TC reduced vascularization in the CAM model, which was associated with the downregulation of VEGFR-2 transcript expression. The present study showed TC to possess anti-angiogenic potential via the inhibition of VEGFR-2. In addition, the study predicted TC to cross BBB as well as a safe alternative for GBM therapy, which needs further investigation.

Interpreting convolutional neural network by joint evaluation of multiple feature maps and an improved NSGA-II algorithm

The ’black box’ characteristics of Convolutional Neural Networks (CNNs) present significant risks to their application scenarios, such as reliability, security, and division of responsibilities. Addressing the interpretability of CNN emerges as an urgent and critical issue in the field of machine learning. Recent research on CNN interpretability has either yielded unstable or inconsistent interpretations, or produced coarse-scale interpretable heatmaps, limiting their applicability in various scenarios. In this work, we propose a novel method of CNNs interpretation by incorporating a joint evaluation of multiple feature maps and employing multi-objective optimization (JE&MOO-CAM). Firstly, a method of joint evaluation for all feature maps is proposed to preserve the complete object instances and improve the overall activation values. Secondly, an interpretation method of CNNs under the MOO framework is proposed to avoid the instability and inconsistency of interpretation. Finally, the operators of selection, crossover, and mutation, along with the method of population initialization in NSGA-II, are redesigned to properly express the characteristics of CNNs. The experimental results, including both qualitative and quantitative assessments along with a sanity check conducted on three classic CNN models—VGG16, AlexNet, and ResNet50—demonstrate the superior performance of the proposed JE&MOO-CAM model. This model not only accurately pinpoints the instances within the image requiring explanation but also preserves the integrity of these instances to the greatest extent possible. These capabilities signify that JE&MOO-CAM surpasses six other leading state-of-the-art methods across four established evaluation criteria.

Evaluating nine different air-sea flux algorithms coupled with CAM6

The accuracy of air-sea flux algorithms significantly impacts the simulation performance of climate models. In this study, we evaluated nine widely-used air-sea flux algorithms: those used in the BCC model, the CAM model, the ECMWF model, and the WRF model (with three options), as well as three other commonly-used algorithms: COARE, UA, and VM. An offline comparison revealed significant discrepancies in the flux calculations obtained with different algorithms. Subsequently, we conducted nine sensitivity experiments by coupling these algorithms into the Community Atmosphere Model version 6 (CAM6) to assess the extent and manner in which the selection of flux algorithms influenced the simulated climate. The online simulations introduced complexities due to interactions between the atmosphere and surface fluxes, making the results more intricate. The iterative process of the model created negative feedback between wind speed and momentum flux, as well as between air temperature and heat flux, leading to inconsistencies between online and offline test results. Based on the comprehensive evaluation metric Distance between Indices of Simulation and Observation (DISO), a concept of combined or segmented algorithm was introduced, and a segmented algorithm based on wind speed was found resulting in an overall superior simulation performance compared to the previous nine experiments.

Research on CNC programming and machining process based on CAD/CAM technology

Abstract Focusing on CNC process data, this paper provides an in-depth analysis, characterization and mining of macro machining processes by associating CAD and CAM models. The article introduces a Bayesian inference method to construct an association relationship between the manufacturing features of the query part and the macroscopic process of the manufactured part, which avoids the need for a direct similarity comparison between the geometry of the query part and the part to be manufactured. In addition, the study calculated the overall similarity between the query part and the CNC programming process data instances through the guidance of the process skeleton, thus realizing the precise evaluation from the CNC programming perspective. The algorithm for generating tool trajectories in multi-axis CNC programming is analyzed. By selecting representative surfaces and performing tool processing calculations, this study explores the process planning and tool parameter selection of usual parts of surfaces in multi-axis CNC programming machining. It optimizes the nonlinear error in tool trajectory processing by combining CAD/CAM technology. The results show that the optimized process proposed in this paper significantly improves the machining efficiency by 36.94%. In the cutting at tool corners, the maximum cutting force generated by the optimized machining process is only 190.3N, which is only 67.2% of the leading cutting force of the Cimatron process. In addition, when the engagement frequency is 780 Hz, the optimized process proposed in this paper has the smallest vibration amplitude, which is only 21.4% of the Cimatron strategy. Therefore, this study significantly improves the machining efficiency while ensuring the machining quality, which has important practical application value.

In vitro and in vivo evaluation of novel chromeno[2,3-d]pyrimidinones as therapeutic agents for triple negative breast cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and the limited therapeutic options show poor efficacy in patients, associated to severe side effects and development of resistance. Considering that chromene-based scaffolds proved to be attractive candidates for cancer therapy, herein we prepared new chromeno[2,3-d]pyrimidinone derivatives by a simple two step procedure, starting from the reaction of cyanoacetamide and a salicylaldehyde. A cell viability screening in several breast cancer cell lines allowed to identify two promising compounds with IC50 values in the low micromolar range for TNBC cells. These chromenes inhibited cell proliferation, induced cell cycle arrest and triggered cell death through apoptosis. In vivo studies revealed a safe profile in invertebrate and vertebrate animal models and confirmed their capacity to inhibit tumor growth in the CAM model, inducing significant tumor regression after 4 days of treatment. The two compounds identified in this study are promising drug candidates for TNBC treatment and valuable hits for future optimization, using the versatile synthetic platform that was developed.

In vivo antiangiogenic effect of nimbolide, trans-chalcone and piperine for use against glioblastoma

BackgroundAngiogenesis is an important hallmark of Glioblastoma (GBM) marked by elevated vascular endothelial growth factor-A (VEGF-A) and its receptor 2 (VEGFR-2). As previously reported nimbolide (NBL), trans-chalcone (TC) and piperine (PPR) possess promising antiangiogenic activity in several cancers however, their comparative efficacy and mechanism of antiangiogenic activity in GBM against VEGFR-2 has not been elucidated.Methods2D and 3D spheroids cultures of U87 (Uppsala 87 Malignant Glioma) were used for evaluation of non-cytotxoic dose for anti-angiogenic activity. The antiangiogenic effect was investigated by the GBM U87 cell line bearing chick CAM model. Excised U87 xenografts were histologically examined for blood vascular density by histochemistry. Reverse transcriptase polymerase chain reaction (RT-PCR) was used to detect the presence of avian and human VEGF-A and VEGFR-2 mRNA transcripts.ResultsUsing 2D and 3D spheroid models, the non-cytotoxic dose of NBL, TC and PPR was ≤ 11 µM. We found NBL, TC and PPR inhibit U87-induced neoangiogenesis in a dose-dependent manner in the CAM stand-alone model as well as in CAM U87 xenograft model. The results also indicate that these natural compounds inhibit the expression of notable angiogenic factors, VEGF-A and VEGFR-2. A positive correlation was found between blood vascular density and VEGF-A as well as VEGFR-2 transcripts.ConclusionTaken together, NBL, TC and PPR can suppress U87-induced neoangiogenesis via a reduction in VEGF-A and its receptor VEGFR-2 transcript expression at noncytotoxic concentrations. These phytochemicals showed their utility as adjuvants to GBM therapy, with Piperine demonstrating superior effectiveness among them all.

Study on Thermal Stability and Fatigue Properties of SBS/CNT-Modified Asphalt Sealant.

Carbon nanotubes (CNTs) and styrene-butadiene-styrene (SBS) are used as reinforcing modifiers in asphalt sealants due to their excellent properties, which can effectively improve the internal structure of the sealant and enhance its mechanical properties. Based on this background, two SBS/CNT-modified asphalt sealants were identified and selected by the orthogonal experimental method and compared with two commercially available sealants. The softening point, flow value, multi-temperature frequency scan test, and multiple stress creep recovery test were used to study the high-temperature rheological properties and aging resistance of four types of sealants. The overall evaluation shows that the proportion of the sealant compound's preparation material is 1% by weight of CNT doping, 5% by weight of SBS doping, and 5% by weight of furfural-extracted-oil doping. The results show that the addition of SBS and CNTs more significantly improves the fatigue resistance of the sealants. With the CAM model, C1.0S5F5 reflects a better relaxation property, which better avoids secondary cracking after the construction of the sealant. With the Burgers model, C1.0S5F5 shows excellent deformation resistance under heavy traffic conditions. In summary, conventional performance indicators, such as the softening point and flow value of SBS/CNT-modified asphalt sealants, can meet the specification requirements and show good high-temperature stability and anti-aging properties compared to commercially available sealants.

CAM Model: Intriguing Natural Bioreactor for Sustainable Research and Reliable/Versatile Testing.

We are witnessing the revival of the CAM model, which has already used been in the past by several researchers studying angiogenesis and anti-cancer drugs and now offers a refined model to fill, in the translational meaning, the gap between in vitro and in vivo studies. It can be used for a wide range of purposes, from testing cytotoxicity, pharmacokinetics, tumorigenesis, and invasion to the action mechanisms of molecules and validation of new materials from tissue engineering research. The CAM model is easy to use, with a fast outcome, and makes experimental research more sustainable since it allows us to replace, reduce, and refine pre-clinical experimentation ("3Rs" rules). This review aims to highlight some unique potential that the CAM-assay presents; in particular, the authors intend to use the CAM model in the future to verify, in a microenvironment comparable to in vivo conditions, albeit simplified, the angiogenic ability of functionalized 3D constructs to be used in regenerative medicine strategies in the recovery of skeletal injuries of critical size (CSD) that do not repair spontaneously. For this purpose, organotypic cultures will be planned on several CAMs set up in temporal sequences, and a sort of organ model for assessing CSD will be utilized in the CAM bioreactor rather than in vivo.

Analytical modeling and experimental verification of churning torque for cam guide rails of 2D piston pump

For 2D piston pump the churning torque of its cam guide rails at high speed is one of the main sources of mechanical efficiency loss. To conveniently calculate the churning torque and also provide guidance for future optimization of churning torque reduction, an accurate analytical model of constant acceleration and constant deceleration cam guide rail assembly of the stacked-rollers 2D piston pump is established, where the whole churning torque is divided into the peripheral churning torque, the pushing flow churning torque, and the end face churning torque. Then the analytical model is verified by CFD simulation preliminarily. Analytical modeling shows that at 16,000 rpm, the churning torque reaches about 0.826 N m, where the peripheral churning torque, the pushing flow churning torque, and the end face churning torque account for about 55.4%, 37.3%, and 7.3% of the total torque respectively, indicating that the structural parameters related to the pushing flow torque should be optimized with first priority at high rotational speed. Finally, the churning torque at 1000–16,000 rpm was experimentally measured and the influence of oil temperature was considered. The experimental results are in good agreement with the results of analytical modeling and CFD simulation, thus verifying the correctness of the proposed analytical model.

In-silico, evolutionary, and functional analysis of CHUP1 and its related proteins in Bienertia sinuspersici-a comparative study across C3, C4, CAM, and SCC4 model plants.

Single-cell C4 (SCC4) plants with bienertioid anatomy carry out photosynthesis in a single cell. Chloroplast movement is the underlying phenomenon, where chloroplast unusual positioning 1 (CHUP1) plays a key role. This study aimed to characterize CHUP1 and CHUP1-like proteins in an SCC4 photosynthetic plant, Bienertia sinuspersici. Also, a comparative analysis of SCC4 CHUP1 was made with C3, C4, and CAM model plants including an extant basal angiosperm, Amborella. The CHUP1 gene exists as a single copy from the basal angiosperms to SCC4 plants. Our analysis identified that Chenopodium quinoa, a recently duplicated allotetraploid, has two copies of CHUP1. In addition, the numbers of CHUP1-like and its associated proteins such as CHUP1-like_a, CHUP1-like_b, HPR, TPR, and ABP varied between the species. Hidden Markov Model analysis showed that the gene size of CHUP1-like_a and CHUP1-like_b of SCC4 species, Bienertia, and Suaeda were enlarged than other plants. Also, we identified that CHUP1-like_a and CHUP1-like_b are absent in Arabidopsis and Amborella, respectively. Motif analysis identified several conserved and variable motifs based on the orders (monocot and dicot) as well as photosynthetic pathways. For instance, CAM plants such as pineapple and cactus shared certain motifs of CHUP1-like_a irrespective of their distant phylogenetic relationship. The free ratio model showed that CHUP1 maintained purifying selection, whereas CHUP1-like_a and CHUP1-like_b have adaptive functions between SCC4 plants and quinoa. Similarly, rice and maize branches displayed functional diversification on CHUP1-like_b. Relative gene expression data showed that during the subcellular compartmentalization process of Bienertia, CHUP1 and actin-binding proteins (ABP) genes showed a similar pattern of expression. Altogether, the results of this study provide insight into the evolutionary and functional details of CHUP1 and its associated proteins in the development of the SCC4 system in comparison with other C3, C4, and CAM model plants.

P-276 Robust and cost effective in-vivo CAM models for drug combination study in colorectal cancer during COVID-19 pandemic

P-276 Robust and cost effective in-vivo CAM models for drug combination study in colorectal cancer during COVID-19 pandemic

Data-Driven and Knowledge-Guided Approach for NC Machining Process Planning

With the wide applications of computer-aided technologies in industries, plenty of process data composed of 3D CAD models and CAM models are increasingly generated, which are the direct and effective carriers of knowledge, intelligence, and experience of skilled designers. However, existing methods cannot effectively learn and mine the implicit and explicit knowledge embedded in process data, and the process scheme generated is difficult to satisfy the manufacturing logics of a part in an industry. In this paper, a data-driven and knowledge-guided approach for NC machining process planning is proposed. First, a multi-level structured NC machining process model based on sub-machining regions is introduced to represent the relations between the 3D CAD model and the CAM model in process data. Then, an attention-based working step sequence generation model is proposed to predict the candidate working step and its associated sub-machining regions. Moreover, a context-free grammar describing the semantic and temporal relationships between working steps is extracted to construct a process knowledge And-Or graph with hierarchy and compositionality (PK-AOG). Finally, guided by PK-AOG, an NC machining process scheme generation method based on grammar parser is proposed to find a joint optimal solution according to the probabilities of the candidate working steps iteratively. A prototype system based on CATIA has been developed to verify the effectiveness of the proposed method.

Pater for Millions

Shaytards was widely considered the original YouTube family vlog, and the family built their massive following with representations of wholesome, heteronormative, religious Americans who could have fun with everyday life. As classic microcelebrities (Senft 2013), the family of six created a valuable brand for millions of fans, which led to fame and wealth. But when the father and driving force of the vlog was caught sending sexually explicit texts to a “cam model”, more than the family brand collapsed. Shay’s persona, as the steady father force for an imagined family (Friedman &amp; Schultermandl 2016) of millions was sent into disarray. This article follows the comments across multiple channels that show how the imagined family negotiated this collapse, demonstrating how an audience can establish a deep personal connection with a microcelebrity’s persona.