Visual Performance of Psychological Factors in Interior Design Under the Background of Artificial Intelligence

Sensation (the reflection of past experience in the mind) is the reflection of the brain on the individual attributes of objective things that directly act on the sense organs. Feeling is the most elementary cognitive process and the simplest psychological phenomenon. Vision is a kind of sense, and sense is produced by objective things acting on the sense organs. But at present, it is rare to analyze interior design exhibition from the perspective of visual psychology, an emerging science, as an interdisciplinary attempt, only in interior design research. Therefore, the study of sensory process should start from its external stimuli, in order to first understand how it acts on the sensory organs to produce sensory phenomena. This paper mainly studies the visual performance of psychological factors in interior design under the background of artificial intelligence. This paper proposes a K-means clustering algorithm and a localization algorithm fused with visual and inertial navigation. The distance thresholds corresponding to the SIFT feature descriptors of threshold T1, 128D, 96D, 64D, and 32D are 170, 160, 150, and 90, respectively. This verifies that the candidate image with the highest number of matching points is considered the best matching image

A General Wasserstein Framework for Data-driven Distributionally Robust Optimization: Tractability and Applications

Data-driven distributionally robust optimization is a recently emerging paradigm aimed at finding a solution that is driven by sample data but is protected against sampling errors. An increasingly popular approach, known as Wasserstein distributionally robust optimization (DRO), achieves this by applying the Wasserstein metric to construct a ball centred at the empirical distribution and finding a solution that performs well against the most adversarial distribution from the ball. In this paper, we present a general framework for studying different choices of a Wasserstein metric and point out the limitation of the existing choices. In particular, while choosing a Wasserstein metric of a higher order is desirable from a data-driven perspective, given its less conservative nature, such a choice comes with a high price from a robustness perspective - it is no longer applicable to many heavy-tailed distributions of practical concern. We show that this seemingly inevitable trade-off can be resolved by our framework, where a new class of Wasserstein metrics, called coherent Wasserstein metrics, is introduced. Like Wasserstein DRO, distributionally robust optimization using the coherent Wasserstein metrics, termed generalized Wasserstein distributionally robust optimization (GW-DRO), has all the desirable performance guarantees: finite-sample guarantee, asymptotic consistency, and computational tractability. The worst-case expectation problem in GW-DRO is in general a nonconvex optimization problem, yet we provide new analysis to prove its tractability without relying on the common duality scheme. Our framework, as shown in this paper, offers a fruitful opportunity to design novel Wasserstein DRO models that can be applied in various contexts such as operations management, finance, and machine learning

Cord blood-derived CD19-specific chimeric antigen receptor T cells: an off-the-shelf promising therapeutic option for treatment of diffuse large B-cell lymphoma

PurposeAutologous chimeric antigen receptor (CAR) T cell therapy is one of the most significant breakthroughs in hematological malignancies. However, a three-week manufacturing cycle and ineffective T cell dysfunction in some patients hinder the widespread application of auto-CAR T cell therapy. Studies suggest that cord blood (CB), with its unique biological properties, could be an optimal source for CAR T cells, providing a product with ‘off-the-shelf’ availability. Therefore, exploring the potential of CB as an immunotherapeutic agent is essential for understanding and promoting the further use of CAR T cell therapy.Experimental designWe used CB to generate CB-derived CD19-targeting CAR T (CB CD19-CAR T) cells. We assessed the anti-tumor capacity of CB CD19-CAR T cells to kill diffuse large B cell lymphoma (DLBCL) in vitro and in vivo.ResultsCB CD19-CAR T cells showed the target-specific killing of CD19+ T cell lymphoma cell line BV173 and CD19+ DLBCL cell line SUDHL-4, activated various effector functions, and inhibited tumor progression in a mouse (BALB/c nude) model. However, some exhaustion-associated genes were involved in off-tumor cytotoxicity towards activated lymphocytes. Gene expression profiles confirmed increased chemokines/chemokine receptors and exhaustion genes in CB CD19-CAR T cells upon tumor stimulation compared to CB T cells. They indicated inherent changes in the associated signaling pathways in the constructed CB CAR T cells and targeted tumor processes.ConclusionCB CD19-CAR T cells represent a promising therapeutic strategy for treating DLBCL. The unique biological properties and high availability of CB CD19-CAR T cells make this approach feasible

Performance optimization of convolution calculation by blocking and sparsity on GPU

Convolution neural network (CNN) plays a paramount role in machine learning, which has made significant contributions in medical image classification, natural language processing, recommender system and so on. A successful convolution neural network can achieve excellent performance with fast execution time. The convolution operation dominates the total operation time of convolution neural network. Therefore, in this paper, we propose a novel convolution method on Graphic Processing Units (GPUs), which reduces the convolution operation time and improves the execution speed by approximately 2X than the state of the art convolution algorithm. Our work is based on the observation that the sparsity of the input feature map of convolution operation is relatively large, and the zero value of the feature map is redundancy for convolution result. Therefore, we skip the zero value calculation and improve the speed by compressing the feature map. Besides, the shape of the feature map for the deep network is small, and the number of threads is limited. Therefore, for a limited number of threads, it is necessary to reduce the amount of calculation to increase the calculation speed. Our algorithm has a good effect on the convolution operation for the feature map of the deep network with large sparsity and small size

An extremely bad-cavity laser

Lasing in the bad-cavity regime has promising applications in precision measurement and frequency metrology due to the reduced sensitivity of the laser frequency to cavity length fluctuations. Thus far, relevant studies have been mainly focused on conventional cavities whose finesse is high enough that the resonance linewidth is sufficiently narrow compared to the cavity's free spectral range, though still in the bad-cavity regime. However, lasing output from the cavity whose finesse is close to the limit of 2 has never been experimentally accessed. Here, we demonstrate an extremely bad-cavity laser, analyze the physical mechanisms limiting cavity finesse, and report on the worst ever laser cavity with finesse reaching 2.01. The optical cavity has a reflectance close to zero and only provides a weak optical feedback. The laser power can be as high as tens of $\mu$W and the spectral linewidth reaches a few kHz, over one thousand times narrower than the gain bandwidth. In addition, the measurement of cavity pulling reveals a pulling coefficient of 0.0148, the lowest value ever achieved for a continuous wave laser. Our findings open up an unprecedentedly innovative perspective for future new ultra-stable lasers, which could possibly trigger the future discoveries in optical clocks, cavity QED, continuous wave superradiant laser, and explorations of quantum manybody physics

A curve model for association of serum homocysteine with carotid artery hemodynamics

Purpose: To investigate the correlation between carotid artery hemodynamics and serum homocysteine.Methods: A total of 894 participants made up of 439 male (49.11 %) and 455 female (50.89 %) from Ma’anshan, China, enrolled in the cross-sectional study. Data collection included demographics, blood sample and carotid ultrasonography. Piecewise linear regression analysis was used to analyze the relationship between serum homocysteine and carotid artery hemodynamics.Results: Homocysteine (Hcy) levels were divided into four groups by quartiles. The populations of the groups were 226, 220, 222, 226; and their mean ages were 56.52 ± 10.49, 62.27 ± 10.06, 63.42 ± 9.81 and 65.38 ± 10.56 years, respectively. After adjustment for blood biochemical and demographics factors, U-shaped and S-shaped curves were as observed between Hcy and carotid artery hemodynamics. The adjusted regression analysis showed that the threshold values of Hcy with end diastolic velocity (EDV) of right common carotid artery (CCA) were 12.50 and 19.00, while for the EDV of right internal carotid artery (ICA), the values were 11.50 and 22.00. U-shaped curves were observed between Hcy and peak systolic velocity (PSV) of left CCA, EDV of left CCA, PSV of left ICA and EDV of left ICA. The threshold values of Hcy with PSV of left CCA, EDV of left CCA, PSV of left ICA and EDV of left ICA were 14.00, 14.00, 14.00 and 13.50, respectively.Conclusion: These results indicate that a significant correlation exists between homocysteine at different concentrations and carotid artery hemodynamics.Keywords: Homocysteine, Hemodynamics, End diastolic velocity, Peak systolic velocit

High-yield production of the human lysozyme by Pichia pastoris SMD1168 using response surface methodology and high-cell-density fermentation

Background: Lysozyme plays a crucial role in innate immunity with its well-recognized bacteriolytic activity. In this study, the influence of expression parameters (inoculation volume, culture volume, growth time, induction temperature and time, initial pH and methanol concentration) on human lysozyme (HLZ) production in recombinant P. pastoris SMD1168 was investigated through Plackett\u2013Burman (PB) design and response surface methodology (RSM). Results: It was revealed that induction temperature, induction time and culture volume had significant influence (P < 0.01) on HLZ expression level, which were elected for further optimization with three-dimensional response surface designs for enhanced HLZ production. The highest lysozyme activity reached 3301 U/mL under optimized conditions (at 23.5\ub0C for 90 h with culture volume of 48 mL) in shake flask, which increased 2.2 fold compared with that achieved with the standard protocol (Invitrogen). When high-cell-density fermentation of the recombinant Pichia pastoris was performed in a 15 L fermenter under optimized conditions, the extracellular lysozyme activity reached 47,680 U/mL. SDS-PAGE analysis of the product demonstrated that HLZ was produced as a single major protein with a molecular weight of approximately 14.7 kDa, consistent with its expected size. Conclusions: The results indicated that the optimized culture conditions using PB design and RSM significantly enhanced the expression level of HLZ, and the Pichia expression system for HLZ production was successful and industrially promising