Does interior color contrast enhance spatial memory?

This study investigated the effect of contrast in neutral-, warm-, and cool-colored spaces on spatial memory. Spatial memory was measured in terms of architectural scale and recollection of architectural elements and furniture. Participants (N = 114) viewed a short virtual simulation video of a residential studio and were asked to sketch a map of the architectural elements on distributed grid paper. Spatial memory was measured in terms of scale, and item recall rate. Contrast and hue had no significant effect on the memorization of proportional scale. However, high-contrast schemes allowed for a significantly higher recollection of architectural elements than low-contrast schemes. In comparing the effect of hues, a significant difference was seen in recalling detailed furniture and lighting items. Participants reported significantly better spatial memory of neutral and warm color schemes than of cool color schemes. There was no interaction effect between contrast and hue in the color combinations. These results can be applied in the design of color schemes for architectural spaces requiring enhanced spatial cognition and memory.     

Extensive evaluation and classification of low-cost dust sensors in laboratory using a newly developed test method

An extensive evaluation of low-cost dust sensors was performed using an exponentially decaying particle concentration. A total of 264 sensors including 27 sensors with light-emitting diodes (LEDs) and 237 sensors with laser lighting sources were tested. Those tested sensors were classified into 4 groups based on the deviation from the reference data obtained by a reference instrument. The response linearities of all the tested samples for PM₁, PM_2.5, and PM₁₀ were in excellent agreement with the reference instrument, except a few samples. For the measurements of PM₁ and PM_2.5, the lighting source, that is, LED or laser, did not show any significant difference in overall sensor performance. However, LED-based sensors did not perform well for PM₁₀ measurements. The 32, 24, and 16% of all the tested sensors for PM₁, PM_2.5, and PM₁₀ measurement, respectively, are in the category of Class 1 (reference instrument reading ± 20%) requirement. The performance of the low-cost dust sensors for PM₁₀ measurement was relatively less satisfactory.     

Shape from focus based on 3D structure tensor using optical microscopy

Shape from focus (SFF) is a widely used passive optical method for 3D shape reconstruction. In SFF, a focus measure, which is used to estimate the relative focus level, plays a critical role in depth estimation. In this article, we present a new focus measure for accurate 3D shape estimation in optical microscopy based on the analysis of 3D structure tensor. First, the 3D tensors are computed from the input image sequence for each pixel. Then, each tensor is decomposed into point, curve, and surface tensors by decomposing tensors into eigenvalues and eigenvectors. Finally, the surfaceness is used to measure the quality of sharpness. The proposed focus measure provides accurate focus values and better resistance against noise. The proposed measure is evaluated by conducting experiments using image sequences of simulated and microscopic real objects. The comparative analysis demonstrates the effectiveness of the proposed focus measure in recovering 3D shape.     

A proposal of novel design on the WAVE MAC algorithm with low-latency for seamless video surveillance in V2X environment

Multimedia Tools and Applications - This paper proposed an MAC (Media Access Control) operation method based on the CCH (Control Channel) and SCH (Service Channel) control mode of the WAVE...     

Study on emotion recognition and companion Chatbot using deep neural network

Multimedia Tools and Applications - With the development of technology, the importance of the research on speech emotion recognition and semantic analysis has increased. The research is primarily...     

Moment Matched Gaussian Kernel and Region Representative Likelihood for Performance Improvement of PMF-based TRN

This paper proposes two techniques to improve the performance of Point Mass Filter (PMF) based Terrain Referenced Navigation (TRN). The first is the kernel     

Continuous emotion estimation of facial expressions on JAFFE and CK+ datasets for human–robot interaction

Human–robot interaction was always based on estimation of human emotions from human facial expressions, voice and gestures. Human emotions were always categorized in a discretized manner, while we estimate facial images from common datasets for continuous emotions. Linear regression was used in this study which numerically quantizes human emotions as valence and arousal by displaying the raw images on the two-respective coordinate axis. The face image datasets from the Japanese female facial expression (JAFFE) dataset and the extended Cohn–Kanade (CK+) dataset were used in this experiment. Human emotions for the above-mentioned datasets were interpreted by 85 participants who were used in the experimentation. The best result from a series of experiments shows that the minimum of root mean square error for the JAFFE dataset was 0.1661 for valence and 0.1379 for arousal. The proposed method has been compared with previous methods such as songs, sentences, and it is observed that the proposed method for common datasets testing showed an outstanding emotion estimation performance.

     

Peptide–Peptide Co-Assembly: A Design Strategy for Functional Detection of C-peptide,A Biomarker of Diabetic Neuropathy

Diabetes-related neuropathy is a debilitating condition that may be averted if it can be detected early. One possible way this can be achieved at low cost is to utilise peptides to detect C-peptide, a biomarker of diabetic neuropathy. This depends on peptide-peptide co-assembly, which is currently in a nascent stage of intense study. Instead, we propose a bead-based triple-overlay combinatorial strategy that can preserve inter-residue information during the screening process for a suitable complementary peptide to co-assemble with C-peptide. The screening process commenced with a pentapeptide general library, which revealed histidine to be an essential residue. Further screening with seven tetrapeptide focused libraries led to a table of self-consistent peptide sequences that included tryptophan and lysine at high frequencies. Three complementary nonapeptides (9mer com-peptides), wpkkhfwgq (Trp-D), kwkkhfwgq (Lys-D), and KWKKHFWGQ (Lys-L) (as a negative control) were picked from this table for co-assembly studies with C-peptide. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) and circular dichroism (CD) spectroscopies were utilized to study inter-peptide interactions and changes in secondary structures respectively. ATR-FTIR studies showed that there is indeed inter-peptide interaction between C-peptide and the tryptophan residues of the 9mer com-peptides. CD studies of unaggregated and colloidal C-peptide with the 9mer com-peptides suggest that the extent of co-assembly of C-peptide with Trp-D is greatest, followed by Lys-D and Lys-L. These results are promising and indicate that the presented strategy is viable for designing and evaluating longer complementary peptides, as well as complementary peptides for co-assembly with other polypeptides of interest and importance. We discuss the possibility of designing complementary peptides to inhibit toxic amyloidosis with this approach.     

NLRP3 Inflammasome Activation Is Involved in LPA1-Mediated Brain Injury after Transient Focal Cerebral Ischemia

Lysophosphatidic acid receptor 1 (LPA₁) contributes to brain injury following transient focal cerebral ischemia. However, the mechanism remains unclear. Here, we investigated whether nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3 (NLRP3) inflammasome activation might be an underlying mechanism involved in the pathogenesis of brain injury associated with LPA₁ following ischemic challenge with transient middle cerebral artery occlusion (tMCAO). Suppressing LPA₁ activity by its antagonist attenuated NLRP3 upregulation in the penumbra and ischemic core regions, particularly in ionized calcium-binding adapter molecule 1 (Iba1)-expressing cells like macrophages of mouse after tMCAO challenge. It also suppressed NLRP3 inflammasome activation, such as caspase-1 activation, interleukin 1β (IL-1β) maturation, and apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) speck formation, in a post-ischemic brain. The role of LPA₁ in NLRP3 inflammasome activation was confirmed in vitro using lipopolysaccharide-primed bone marrow-derived macrophages, followed by LPA exposure. Suppressing LPA₁ activity by either pharmacological antagonism or genetic knockdown attenuated NLRP3 upregulation, caspase-1 activation, IL-1β maturation, and IL-1β secretion in these cells. Furthermore, nuclear factor-κB (NF-κB), extracellular signal-regulated kinase 1/2 (ERK1/2), and p38 were found to be LPA₁-dependent effector pathways in these cells. Collectively, results of the current study first demonstrate that LPA₁ could contribute to ischemic brain injury by activating NLRP3 inflammasome with underlying effector mechanisms.