Co-Treatment with Phlorotannin and Extracellular Vesicles from Ecklonia cava Inhibits UV-Induced Melanogenesis.

Hyperpigmentation due to ultraviolet (UV)-induced melanogenesis causes various esthetic problems. Phlorotannin (PT) and extracellular vesicles (EVs) derived from various plants suppress melanogenesis pathways. We used UV-exposed keratinocytes and animal skin to determine if co-treatment with PT and EVs from Ecklonia cava (EVE) could inhibit melanogenesis by reducing UV-induced oxidative stress and the expression of the thioredoxin-interacting protein (TXNIP)/nucleotide-binding oligomerization domain-like receptor family pyrin domain containing the 3 (NLRP3)/interleukin-18 (IL-18) pathway, which are upstream signals of the microphthalmia-associated transcription factor. UV exposure increased oxidative stress in keratinocytes and animal skin, as evaluated by 8-OHdG expression, and this effect was reduced by co-treatment with PT and EVE. UV also increased binding between NLRP3 and TXNIP, which increased NLRP3 inflammasome activation and IL-18 secretion, and this effect was reduced by co-treatment with PT and EVE in keratinocytes and animal skin. In melanocytes, conditioned media (CM) from UV-exposed keratinocytes increased the expression of melanogenesis-related pathways; however, these effects were reduced with CM from UV-exposed keratinocytes treated with PT and EVE. Similarly, PT and EVE treatment reduced melanogenesis-related signals, melanin content, and increased basement membrane (BM) components in UV-exposed animal skin. Thus, co-treatment with PT and EVE reduced melanogenesis and restored the BM structure by reducing oxidative stress and TXNIP/NLRP3/IL-18 pathway expression.

Optimal bilayer composites for temperature-tracking wireless electronics.

Modern silicone-based epidermal electronics engineered for body temperature sensing represent a pivotal development in the quest for advancing preventive medicine and enhancing post-surgical monitoring. While these compact and highly flexible electronics empower real-time monitoring in dynamic environments, a noteworthy limitation is the challenge in regulating the infiltration or obstruction of heat from the external environment into the surface layers of these electronics. The study presents a cost-effective temperature sensing solution by embedding wireless electronics in a multi-layered elastomeric composite to meet the dual needs of enhanced thermal insulation for encapsulation in contact with air and improved thermal conductivity for the substrate in contact with the skin. The encapsulating composite benefits from the inclusion of hollow silica microspheres, which reduce the thermal conductivity by 40%, while non-spherical aluminum nitride enhances the thermal conductivity of the substrate by 370%. The addition of particles to the respective composites inevitably leads to an increase in modulus. Two composite elements are engineered to coexist while maintaining a matching low modulus of 3.4 MPa and a stretchability exceeding 30%, all without compromising the optimized thermal properties. Consecutive thermal, electrical, and mechanical characterization confirms the sensor's capacity for precise body temperature monitoring during a single day's lifespan, while also assessing the influence of behavioral factors on body temperature.

Different development and fecundity between Spodoptera frugiperda USA and China populations, influenced by ecdysone-related genes.

The fall armyworm (FAW), Spodoptera frugiperda, is one of the most harmful plant pests in the world and is globally distributed from the American continent to the Asian region. The FAW USA population (Sf-USA) and China population (Sf-CHN), which belong to corn strain, showed different developmental periods and fecundity rates in lab conditions. Sf-USA had faster development and higher fecundity compared with Sf-CHN. To examine these differences, transcriptomic data from two FAW populations were analyzed and compared. Twelve gigabytes of transcripts were read from each sample and 21,258 differentially expressed genes (DEGs) were detected. DEGs with log2 fold change ≥ 2 were identified and compared in two populations. In comparison to the Sf-CHN, we discovered that 3471 and 3851 individual DEGs upregulated and downregulated, respectively. Comparing transcriptome profiles for differential gene expression revealed several DEGs, including 39 of ecdysone (E)-, 25 of juvenile hormone-, and 15 of insulin-related genes. We selected six of E-related genes, such as Neverland, Shade, Ecdysone receptor, Ecdysone-inducible protein 74 (E74), E75, and E78 from DEGs. Gene expressions were suppressed by RNA interference to confirm the physiological functions of the selected genes from Sf-USA. The Sf-USA showed developmental retardation and a decrease in fecundity rate by suppression of E-related genes. These findings show that biological characteristics between Sf-USA and Sf-CHN are influenced by E-related genes.

Insights on reproduction-related genes in the striped fruit fly, Zeugodacus scutellata (Hendel) (Diptera: Tephritidae).

The striped fruit fly, Zeugodacus scutellata is a significant pest in East and Southeast Asia by damaging Cucurbitaceae blossoms and fruits. To control this pest, a novel strategy to suppress the gene(s) associated with sexually dimorphic phenotypes has been devised and implemented in a laboratory scale. However, comprehensive transcriptomic analysis related to this sex differentiation of Z. scutellata was necessary to determine effective target genes for the genetic control. We performed de novo assembly of the transcript obtained by paired-end sequencing using an Illumina HiSeq platform and let to 217,967 unigenes (i.e., unique genes) with a minimum length of 200 bp. The female produced 31, 604, 442 reads with 97.93% of Q20, 94.76% of Q30, and the male produced 130, 592, 828 reads with 97.93% of Q20 and 94.76 of Q30%. The differentially expressed genes were used to predict genetic factors associated with sex differentiation, which included Rho1, extra-macrochaetae (emc), hopscotch (hop), doublesex (dsx), sex-lethal (sxl), transformer-2 (tra-2), testis-specific serine/threonine-protein kinase (tssk1), tektin1 (tkt1) and 2 (tkt2), odorant binding proteins (OBPs), fruitless (fru), vitellogenin receptor, and hormone receptors in Z. scutellata. In addition, this transcriptome analysis provides the additional gene associated with sex determination and mating behaviors, which would be applied to develop a novel sterile insect technique against Z. scutellata.

Species-specific wiring of cortical circuits for small-world networks in the primary visual cortex.

Long-range horizontal connections (LRCs) are conspicuous anatomical structures in the primary visual cortex (V1) of mammals, yet their detailed functions in relation to visual processing are not fully understood. Here, we show that LRCs are key components to organize a "small-world network" optimized for each size of the visual cortex, enabling the cost-efficient integration of visual information. Using computational simulations of a biologically inspired model neural network, we found that sparse LRCs added to networks, combined with dense local connections, compose a small-world network and significantly enhance image classification performance. We confirmed that the performance of the network appeared to be strongly correlated with the small-world coefficient of the model network under various conditions. Our theoretical model demonstrates that the amount of LRCs to build a small-world network depends on each size of cortex and that LRCs are beneficial only when the size of the network exceeds a certain threshold. Our model simulation of various sizes of cortices validates this prediction and provides an explanation of the species-specific existence of LRCs in animal data. Our results provide insight into a biological strategy of the brain to balance functional performance and resource cost.

Phylogeny and lipid profiles of snow-algae isolated from Norwegian red-snow microbiomes.

Snow algae blooms often form green or red coloured patches in melting alpine and polar snowfields worldwide, yet little is known about their biology, biogeography, and species diversity. We investigated eight isolates collected from red snow in northern Norway, using a combination of morphology, 18S rRNA gene and internal transcribed spacer 2 (ITS2) genetic markers. Phylogenetic and ITS2 rRNA secondary structure analyses assigned six isolates to the species Raphidonema nivale, Deuterostichococcus epilithicus, Chloromonas reticulata, and Xanthonema bristolianum. Two novel isolates belonging to the family Stichococcaceae (ARK-S05-19) and the genus Chloromonas (ARK-S08-19) were identified as potentially new species. In laboratory cultivation, differences in the growth rate and fatty acid profiles were observed between the strains. Chlorophyta were characterized by abundant C18:3n-3 fatty-acids with increases in C18:1n-9 in the stationary phase, whilst Xanthonema (Ochrophyta) was characterized by a large proportion of C20:5n-3, with increases in C16:1n-7 in the stationary phase. In a further experiment, lipid droplet formation was studied in C. reticulata at the single-cell level using imaging flow cytometry. Our study establishes new cultures of snow algae, reveals novel data on their biodiversity and biogeography, and provides an initial characterization of physiological traits that shape natural communities and their ecophysiological properties.

AI Model for Detection of Abdominal Hemorrhage Lesions in Abdominal CT Images.

Information technology has been actively utilized in the field of imaging diagnosis using artificial intelligence (AI), which provides benefits to human health. Readings of abdominal hemorrhage lesions using AI can be utilized in situations where lesions cannot be read due to emergencies or the absence of specialists; however, there is a lack of related research due to the difficulty in collecting and acquiring images. In this study, we processed the abdominal computed tomography (CT) database provided by multiple hospitals for utilization in deep learning and detected abdominal hemorrhage lesions in real time using an AI model designed in a cascade structure using deep learning, a subfield of AI. The AI model was used a detection model to detect lesions distributed in various sizes with high accuracy, and a classification model that could screen out images without lesions was placed before the detection model to solve the problem of increasing false positives owing to the input of images without lesions in actual clinical cases. The developed method achieved 93.22% sensitivity and 99.60% specificity.

Suboptimal controller design of global active noise control system for various acoustic environments.

Conventional active noise control (ANC) systems in enclosed spaces are not easy to implement experimentally because they require a large number of microphones to measure sound pressure in global areas. Even if such systems are possible, if there are any changes in the locations of noise sources or surrounding objects, or if ANC system moves to another enclosed space, an expensive and time-consuming experimental calibration is again required. Implementation of global ANC in enclosed spaces is thus difficult. Therefore, we designed a global ANC system that can be used in various acoustic environments. The main idea involves suboptimal open-loop controller design in the free field. By using an open-loop controller, a controller calibrated once can be used in various acoustic environments. A controller designed in the free field derive a suboptimal solution without bias toward a specific acoustic environment. For controller design in the free field, we propose an experimental calibration approach in which the arrangement and the number of control speakers and microphones are determined by the frequency range and radiation pattern of the noise source. We conducted simulations and experiments to show that the designed controller in the free field is sufficiently effective in other enclosed spaces.

Phenylalanine Ammonia-Lyase: A Key Gene for Color Discrimination of Edible Mushroom Flammulina velutipes.

In nature; Flammulina velutipes, also known as winter mushrooms, vary in the color of their fruiting bodies, from black, yellow, pale yellow, or beige to white. The purpose of this study was to compare the genome sequences of different colored strains of F. velutipes and to identify variations in the genes associated with fruiting body color. Comparative genomics of six F. velutipes strains revealed 70 white-strain-specific variations, including single nucleotide polymorphisms (SNPs) and insertions/deletions (indels), in the genome sequences. Among them, 36 variations were located in the open reading frames, and only one variation was identified as a mutation with a disruptive in-frame deletion (ΔGCGCAC) within the annotated gene phenylalanine ammonia-lyase 1 (Fvpal1). This mutation was found to cause a deletion, without a frameshift, of two amino acids at positions 112 and 113 (arginine and threonine, respectively) in the Fvpal1 gene of the white strain. Specific primers to detect this mutation were designed, and amplification refractory mutation system (ARMS) polymerase chain reaction (PCR) was performed to evaluate whether the mutation is color specific for the F. velutipes fruiting body. PCR analysis of a total of 95 F. velutipes strains revealed that this mutation was present only in white strains. In addition, monospores of the heterozygous mutant were isolated, and whether this mutation was related to the color of the fruiting body was evaluated by a mating assay. In the mating analysis of monospores with mutations in Fvpal1, it was found that this mutation plays an important role in determining the color of the fruiting body. Furthermore, the deletion (Δ112RT113) in Fvpal1 is located between motifs that play a key role in the catalytic function of FvPAL1. These results suggest that this mutation can be used as an effective marker for the color-specific breeding of F. velutipes, a representative edible mushroom.

Circular active noise barrier using theoretical control filter considering interaction between speaker and barrier.

A circular active noise barrier using a theoretically calculated control filter without real-time adaptation was proposed for noise reduction in a specific outdoor space. A compact circular barrier is used for the movable system to cope with changes in the location of the workspace, and noise in a wide frequency band can be reduced by conducting active noise control through control speakers arranged around a barrier. However, there was a significant performance gap compared with the maximum performance achieved by using the experimental fixed filter due to an extremely simplified theoretical model which ignores the interaction between the control speakers and the barrier. Therefore, this study tried to minimize the performance degradation when applying the theoretically calculated control filter. Another theoretical model is introduced to improve the noise reduction performance by considering the interaction between the control speaker and the barrier. Through experiment, it is confirmed that noise reduction performance is improved by about 2.6 dB in the frequency of interest.

Antioxidant and anti-photoaging effects of a fucoidan isolated from Turbinaria ornata.

Fucoidans isolated from brown seaweeds are potential ingredients in the cosmetic industry. In our preosvious study, a fucoidan was isolated from the brown seaweed Turbinaria ornata (TO-F10) and the anti-inflammatory effect of TO-F10 was evaluated. In order to further explore the potential of TO-F10 in cosmetics, in the present study, antioxidant and photoprotective effects of TO-F10 were investigated. TO-F10 remarkably protected Vero cells against AAPH-stimulated cell death by reducing apoptosis via scavenging intracellular reactive oxygen species (ROS). In addition, TO-F10 increased the survival rate of AAPH-treated zebrafish by suppressing oxidative stress displayed in reducing the levels of ROS, cell death, and lipid peroxidation. Furthermore, TO-F10 effectively attenuated UVB-induced in vitro and in vivo photodamage. TO-F10 increased the viability of UVB-irradiated human keratinocytes via suppressing apoptosis by reducing the intracellular ROS level. Besides, TO-F10 effectively attenuated in vivo photodamage stimulated by UVB irradiation via inhibiting oxidative stress and inflammatory response in zebrafish. These results demonstrate that TO-F10 possesses in vitro and in vivo antioxidant and photoprotective effects, and suggest TO-F10 is a potential ingredient in the cosmetic industry.

Improving quality control in the routine practice for histopathological interpretation of gastrointestinal endoscopic biopsies using artificial intelligence.

BACKGROUND: Colorectal and gastric cancer are major causes of cancer-related deaths. In Korea, gastrointestinal (GI) endoscopic biopsy specimens account for a high percentage of histopathologic examinations. Lack of a sufficient pathologist workforce can cause an increase in human errors, threatening patient safety. Therefore, we developed a digital pathology total solution combining artificial intelligence (AI) classifier models and pathology laboratory information system for GI endoscopic biopsy specimens to establish a post-analytic daily fast quality control (QC) system, which was applied in clinical practice for a 3-month trial run by four pathologists. METHODS AND FINDINGS: Our whole slide image (WSI) classification framework comprised patch-generator, patch-level classifier, and WSI-level classifier. The classifiers were both based on DenseNet (Dense Convolutional Network). In laboratory tests, the WSI classifier achieved accuracy rates of 95.8% and 96.0% in classifying histopathological WSIs of colorectal and gastric endoscopic biopsy specimens, respectively, into three classes (Negative for dysplasia, Dysplasia, and Malignant). Classification by pathologic diagnosis and AI prediction were compared and daily reviews were conducted, focusing on discordant cases for early detection of potential human errors by the pathologists, allowing immediate correction, before the pathology report error is conveyed to the patients. During the 3-month AI-assisted daily QC trial run period, approximately 7-10 times the number of slides compared to that in the conventional monthly QC (33 months) were reviewed by pathologists; nearly 100% of GI endoscopy biopsy slides were double-checked by the AI models. Further, approximately 17-30 times the number of potential human errors were detected within an average of 1.2 days. CONCLUSIONS: The AI-assisted daily QC system that we developed and established demonstrated notable improvements in QC, in quantitative, qualitative, and time utility aspects. Ultimately, we developed an independent AI-assisted post-analytic daily fast QC system that was clinically applicable and influential, which could enhance patient safety.

An Effective Design Formula for Single-Layer Printed Spiral Coils with the Maximum Quality Factor (Q-Factor) in the Megahertz Frequency Range.

This paper presents a design formula for a printed spiral coil to ensure the maximum quality factor (Q-factor). The formula is composed of a pattern's metal thickness, single pattern width, total pattern width, and turn number, and is effective in the megahertz (MHz) frequency range. During the formula's design, the resistance, self-inductance, and Q-factor are calculated according to the ratio of each pattern's width and total pattern width and the turn number for different metal thicknesses, frequencies, and total pattern widths using a volume filament model (VFM). With a given turn number and metal thickness, the optimal ratio of individual and total pattern widths can be determined to ensure the maximum Q-factor. To verify the formula, some optimal coils were fabricated, and the calculations and measurements were shown to have good agreement. Furthermore, the optimized coils were shown to have higher coupling efficiency than the coils without optimal dimensions.

Integrated Biological Control Using a Mixture of Two Entomopathogenic Bacteria, Bacillus thuringiensis and Xenorhabdus hominickii, against Spodoptera exigua and Other Congeners.

Insect immunity defends against the virulence of various entomopathogens, including Bacillus thuringiensis (Bt). This study tested a hypothesis that any suppression of immune responses enhances Bt virulence. In a previous study, the entomopathogenic bacterium, Xenorhabdus hominickii (Xh), was shown to produce secondary metabolites to suppress insect immune responses. Indeed, the addition of Xh culture broth (XhE) significantly enhanced the insecticidal activity of Bt against S. exigua. To analyze the virulence enhanced by the addition of Xh metabolites, four bacterial secondary metabolites were individually added to the Bt treatment. Each metabolite significantly enhanced the Bt insecticidal activity, along with significant suppression of the induced immune responses. A bacterial mixture was prepared by adding freeze-dried XhE to Bt spores, and the optimal mixture ratio to kill the insects was determined. The formulated bacterial mixture was applied to S. exigua larvae infesting Welsh onions in a greenhouse and showed enhanced control efficacy compared to Bt alone. The bacterial mixture was also effective in controlling other Spodopteran species such as S. litura and S. frugiperda but not other insect genera or orders. This suggests that Bt+XhE can effectively control Spodoptera-associated pests by suppressing the immune defenses.

Anti-Arthritogenic Property of Interleukin 10-Expressing Human Amniotic MSCs Generated by Gene Editing in Collagen-Induced Arthritis.

Although stem cells are promising tools for the treatment of arthritis, their therapeutic effects remain controversial. In this study, we investigated the therapeutic properties of interleukin (IL)-10-overexpressing human amniotic mesenchymal stem cells (AMMs) generated via gene editing in a collagen-induced mouse model. IL-10 was inserted into the genomic loci of AMMs via transcription activator-like effector nucleases. In vitro immunomodulatory effects of IL-10-overexpressing AMMs (AMM/I) were evaluated and their anti-arthritogenic properties were determined in collagen-induced arthritis (CIA) mice. Transplantation of AMM/I attenuates CIA progression. In addition, the regulatory T cell population was increased, while T helper-17 cell activation was suppressed by AMM/I administration in CIA mice. Consistently, AMM/I injection increased proteoglycan expression, while reducing inflammation and the expression levels of the pro-inflammatory factors, IL-1 ß, IL-6, monocyte chemoattractant protein-1, and tumor necrosis factor- α, in joint tissues. In conclusion, use of IL-10-edited human AMM/I may be a novel therapeutic strategy for the treatment of arthritis.

MixPatch: A New Method for Training Histopathology Image Classifiers.

CNN-based image processing has been actively applied to histopathological analysis to detect and classify cancerous tumors automatically. However, CNN-based classifiers generally predict a label with overconfidence, which becomes a serious problem in the medical domain. The objective of this study is to propose a new training method, called MixPatch, designed to improve a CNN-based classifier by specifically addressing the prediction uncertainty problem and examine its effectiveness in improving diagnosis performance in the context of histopathological image analysis. MixPatch generates and uses a new sub-training dataset, which consists of mixed-patches and their predefined ground-truth labels, for every single mini-batch. Mixed-patches are generated using a small size of clean patches confirmed by pathologists while their ground-truth labels are defined using a proportion-based soft labeling method. Our results obtained using a large histopathological image dataset shows that the proposed method performs better and alleviates overconfidence more effectively than any other method examined in the study. More specifically, our model showed 97.06% accuracy, an increase of 1.6% to 12.18%, while achieving 0.76% of expected calibration error, a decrease of 0.6% to 6.3%, over the other models. By specifically considering the mixed-region variation characteristics of histopathology images, MixPatch augments the extant mixed image methods for medical image analysis in which prediction uncertainty is a crucial issue. The proposed method provides a new way to systematically alleviate the overconfidence problem of CNN-based classifiers and improve their prediction accuracy, contributing toward more calibrated and reliable histopathology image analysis.

Validity of OSCE Evaluation Using the FLEX Model of Blended Learning.

BACKGROUND: For OSCE (Objective Structured Clinical Examination) scoring, medical schools must bring together many clinical experts at the same place, which is very risky in the context of the coronavirus pandemic. However, if the FLEX model with the properties of self-directed learning and offline feedback is applied to OSCE, it is possible to provide a safe and effective evaluation environment for both universities and students through experts' evaluation of self-video clips of medical students. The present study investigated validity of the FLEX model to evaluate OSCE in a small group of medical students. METHODS: Sixteen 3rd grade medical students who failed on OSCE were required to take a make-up examination by videotaping the failed items and submitting them online. The scores between original examination and make-up examination were compared using Paired Wilcoxon Signed Rank Test, and a post-hoc questionnaire was conducted. RESULTS: The score for make-up examination was significantly higher than those for original examination. The significance was maintained even when the score was compared by individual domains of skills and proficiency. In terms of preference, students were largely in favor of self-videotaped examination primarily due to the availability of self-practice. CONCLUSION: The FLEX model can be effectively applied to medical education, especially for evaluation of OSCE.

Suppression of PBAN receptor expression reduces fecundity in the fall armyworm, Spodoptera frugiperda.

The fall armyworm, Spodoptera frugiperda, native to the tropical and subtropical areas of the American continent is one of the world's most destructive insect pests. In most insects, sex pheromone production is initiated following the activation of a pheromone-biosynthesis-activating neuropeptide (PBAN) receptor, which belongs to G protein-coupled receptor. We explored expression level of S. frugiperda PBAN receptor (Sf-PBANr) gene and validated the physiological function by assessing the fecundity of adult females subjected to its specific RNA interference (RNAi). Sf-PBANr was predicted from a transcriptome of S. frugiperda. Reverse-transcription polymerase chain reaction assay showed its expression in all developmental stages of S. frugiperda. Specific suppression of Sf-PBANr by RNAi in either sex significantly reduced the total number of laid eggs per adult female. Matings between both RNAi-treated males and female resulted in 63.3% reduction in fecundity. In contrast, the RNAi effect was less 47.5%-49.5% at the matings from single-parent RNAi treatment. These results suggest that the Sf-PBANr is associated with female of S. frugiperda.

Presenilin 2 N141I mutation induces hyperactive immune response through the epigenetic repression of REV-ERBα.

Hyperimmunity drives the development of Alzheimer disease (AD). The immune system is under the circadian control, and circadian abnormalities aggravate AD progress. Here, we investigate how an AD-linked mutation deregulates expression of circadian genes and induces cognitive decline using the knock-in (KI) mice heterozygous for presenilin 2 N141I mutation. This mutation causes selective overproduction of clock gene-controlled cytokines through the DNA hypermethylation-mediated repression of REV-ERBα in innate immune cells. The KI/+ mice are vulnerable to otherwise innocuous, mild immune challenges. The antipsychotic chlorpromazine restores the REV-ERBα level by normalizing DNA methylation through the inhibition of PI3K/AKT1 pathway, and prevents the overexcitation of innate immune cells and cognitive decline in KI/+ mice. These results highlight a pathogenic link between this AD mutation and immune cell overactivation through the epigenetic suppression of REV-ERBα.

Multiple-Actuator Fault Isolation Using a Minimal ℓ1-Norm Solution with Applications in Overactuated Electric Vehicles.

A multiple-actuator fault isolation approach for overactuated electric vehicles (EVs) is designed with a minimal ℓ1-norm solution. As the numbers of driving motors and steering actuators increase beyond the number of controlled variables, an EV becomes an overactuated system, which exhibits actuator redundancy and enables the possibility of fault-tolerant control (FTC). On the other hand, an increase in the number of actuators also increases the possibility of simultaneously occurring multiple faults. To ensure EV reliability while driving, exact and fast fault isolation is required; however, the existing fault isolation methods demand high computational power or complicated procedures because the overactuated systems have many actuators, and the number of simultaneous fault occurrences is increased. The method proposed in this paper exploits the concept of sparsity. The underdetermined linear system is defined from the parity equation, and fault isolation is achieved by obtaining the sparsest nonzero component of the residuals from the minimal ℓ1-norm solution. Therefore, the locations of the faults can be obtained in a sequence, and only a consistently low computational load is required regardless of the isolated number of faults. The experimental results obtained with a scaled-down overactuated EV support the effectiveness of the proposed method, and a quantitative index of the sparsity condition for the target EV is discussed with a CarSim-connected MATLAB/Simulink simulation.