Video2Haptics: Converting Video Motion to Dynamic Haptic Feedback with Bio-Inspired Event Processing.

In cinematic VR applications, haptic feedback can significantly enhance the sense of reality and immersion for users. The increasing availability of emerging haptic devices opens up possibilities for future cinematic VR applications that allow users to receive haptic feedback while they are watching videos. However, automatically rendering haptic cues from real-time video content, particularly from video motion, is a technically challenging task. In this paper, we propose a novel framework called "Video2Haptics" that leverages the emerging bio-inspired event camera to capture event signals as a lightweight representation of video motion. We then propose efficient event-based visual processing methods to estimate force or intensity from video motion in the event domain, rather than the pixel domain. To demonstrate the application of Video2Haptics, we convert the estimated force or intensity to dynamic vibrotactile feedback on emerging haptic gloves, synchronized with the corresponding video motion. As a result, Video2Haptics allows users not only to view the video but also to perceive the video motion concurrently. Our experimental results show that the proposed event-based processing methods for force and intensity estimation are one to two orders of magnitude faster than conventional methods. Our user study results confirm that the proposed Video2Haptics framework can considerably enhance the users' video experience.

Biomimetic Adaptive Pure Pursuit Control for Robot Path Tracking Inspired by Natural Motion Constraints.

The essence of biomimetics in human-computer interaction (HCI) is the inspiration derived from natural systems to drive innovations in modern-day technologies. With this in mind, this paper introduces a biomimetic adaptive pure pursuit (A-PP) algorithm tailored for the four-wheel differential drive robot (FWDDR). Drawing inspiration from the intricate natural motions subjected to constraints, the FWDDR's kinematic model mirrors non-holonomic constraints found in biological entities. Recognizing the limitations of traditional pure pursuit (PP) algorithms, which often mimic a static behavioral approach, our proposed A-PP algorithm infuses adaptive techniques observed in nature. Integrated with a quadratic polynomial, this algorithm introduces adaptability in both lateral and longitudinal dimensions. Experimental validations demonstrate that our biomimetically inspired A-PP approach achieves superior path-following accuracy, mirroring the efficiency and fluidity seen in natural organisms.

Ubiquitin-Conjugating Enzyme OsUBC11 Affects the Development of Roots via Auxin Pathway.

Rice has 48 ubiquitin-conjugating enzymes, and the functions of most of these enzymes have not been elucidated. In the present study, a T-DNA insertional mutant named R164, which exhibited a significant decrease in the length of primary and lateral roots, was used as the experimental material to explore the potential function of OsUBC11. Analysis using the SEFA-PCR method showed that the T-DNA insertion was present in the promoter region of OsUBC11 gene, which encodes ubiquitin-conjugating enzyme (E2), and activates its expression. Biochemical experiments showed that OsUBC11 is a lysine-48-linked ubiquitin chain-forming conjugase. OsUBC11 overexpression lines showed the same root phenotypes. These results demonstrated that OsUBC11 was involved in root development. Further analyses showed that the IAA content of R164 mutant and OE3 line were significantly lower compared with wild-type Zhonghua11. Application of exogenous NAA restored the length of lateral and primary roots in R164 and OsUBC11 overexpression lines. Expression of the auxin synthesis regulating gene OsYUCCA4/6/7/9, the auxin transport gene OsAUX1, auxin/indole-3-acetic acid (Aux/IAA) family gene OsIAA31, auxin response factor OsARF16 and root regulator key genes, including OsWOX11, OsCRL1, OsCRL5 was significantly down-regulated in OsUBC11 overexpressing plants. Collectively, these results indicate that OsUBC11 modulates auxin signaling, ultimately affecting root development at the rice seedling stage.

Progress in Data Acquisition of Wearable Sensors.

Wearable sensors have demonstrated wide applications from medical treatment, health monitoring to real-time tracking, human-machine interface, smart home, and motion capture because of the capability of in situ and online monitoring. Data acquisition is extremely important for wearable sensors, including modules of probes, signal conditioning, and analog-to-digital conversion. However, signal conditioning, analog-to-digital conversion, and data transmission have received less attention than probes, especially flexible sensing materials, in research on wearable sensors. Here, as a supplement, this paper systematically reviews the recent progress of characteristics, applications, and optimizations of transistor amplifiers and typical filters in signal conditioning, and mainstream analog-to-digital conversion strategies. Moreover, possible research directions on the data acquisition of wearable sensors are discussed at the end of the paper.

OsASHL1 and OsASHL2, two members of the COMPASS-like complex, control floral transition and plant development in rice.

COMPASS or COMPASS-like is a highly conserved polyprotein complex in eukaryotes that is often involved in methylation of histone H3 lysine 4 (H3K4). However, the biological function of this complex in rice (Oryza sativa) is unclear. Here, we report the identifiction of their functions in growth and development. The osashl1 osashl2 double mutant shows a dwarf and late-flowering phenotype. Lower expression of Ehd1, OsVIL4, and OsMADS51 in the osashl1 osashl2 double mutant background accompanies a delayed vegetative growth phase and photoperiod-sensitive phase compared with that in wild type. Notably, there is less H3K4 mono-, di- and tri-methylation genome-wide in the double mutant, in particular less H3K4 tri-methylation at OsVIL4. Consistent with this result, knockout of OsVIL4 gives rise to a late-flowering phenotype similar to that of the osashl1 osashl2 double mutant, suggesting that OsVIL4 is a target of the COMPASS-like complex. In addition, the expression of key genes in brassinosteroid and gibberellic acid metabolism is altered in the osashl1 osashl2 double mutant, suggesting that the COMPASS-like complex regulates plant growth and development by modulating the levels of these two phytohormones. In summary, we demonstrate that OsASHL1 and OsASHL2 are important for floral transition and plant development.

Overexpression of the rice ORANGE gene OsOR negatively regulates carotenoid accumulation, leads to higher tiller numbers and decreases stress tolerance in Nipponbare rice.

The ORANGE (OR) gene has been reported to regulate chromoplast differentiation and enhance carotenoid biosynthesis in many dicotyledonous plants. However, the function of the OR gene in monocotyledons, especially rice, is poorly known. Here, the OR gene from rice, OsOR, was isolated and characterized by generating overexpressing and genome editing mutant lines. The OsOR-overexpressing plants exhibited pleiotropic phenotypes, such as alternating transverse green and white sectors on leaves at the early tillering stage, that were due to changes in thylakoid development and reduced carotenoid content. In addition, the number of tillers significantly increased in OsOR-overexpressing plants but decreased in osor mutant lines, a result similar to that previously reported for the carotenoid isomerase mutant mit3. The expression of the DWARF3 and DWARF53 genes that are involved in the strigolactone signalling pathway were similarly downregulated in OsOR-overexpressing plants but upregulated in osor mutants. Moreover, the OsOR-overexpressing plants exhibited greater sensitivity to salt and cold stress, and had lower total chlorophyll and higher MDA contents. All results suggest that the OsOR gene plays an important role not only in carotenoid accumulation but also in tiller number regulation and in responses to environmental stress in rice.

[Effects of Biochar on Nitrous Oxide Fluxes and the Abundance of Related Functional Genes from Agriculture Soil in the North China Plain].

To explore the effect and mechanism of biochar application in reducing nitrous oxide (N2O) content in agricultural soil, from March 27 to June 5 2015, pot experiments were conducted to study the effects of biochar application rates (CK, C1:5%, C2:10%, C3:15%, and C4:30%) (mass fraction) on soil N2O fluxes and the functional marker genes ammonia monooxygenase (amoA), nirK, nirS, and nosZ, which are responsible for nitrification and denitrification. The results revealed the following. ①The application of low doses of biochar (5%) promoted N2O emission. The application of middle and high doses of biochar reduced N2O emission. Furthermore, the application of biochar (15%) was found to be the best practice to reduce N2O emission. ② At the beginning of the experiment, biochar had a significant effect on the abundance of soil amoA and denitrification bacteria gene. Furthermore, the abundance of AOA and nirS had a significant positive correlation with the biochar rate, and the abundance of nirK gene and biochar rate were significant. There was a significant negative correlation between AOB and nosZ gene abundance and biochar rate. At the end of the experiment, AOA abundance correlated negatively with biochar rate, while there was a significantly positive relationship between AOB abundance and biochar rate. ③ At the beginning of the experiment, the N2O fluxes exhibited a significant negative correlation with AOA and nirS gene, indicating that N2O production was controlled by the abundance of AOA and nirS gene under high soil moisture content. At the end of the experiment, there was a significant positive correlation between N2O flux and nosZ gene, indicating that the production of N2O was regulated by the abundance of nosZ gene under low soil water content. The results of this study showed that the application of biochar altered the abundance of amoA and denitrification bacteria genes, and reduced N2O emission. These results provide a theoretical basis for a rational application of biochar in farmland.

Highly efficient isolation and release of circulating tumor cells based on size-dependent filtration and degradable ZnO nanorods substrate in a wedge-shaped microfluidic chip.

Circulating tumor cells (CTCs) have been regarded as the major cause of metastasis, holding significant insights for tumor diagnosis and treatment. Although many efforts have been made to develop methods for CTC isolation and release in microfluidic system, it remains significant challenges to realize highly efficient isolation and gentle release of CTCs for further cellular and bio-molecular analyses. In this study, we demonstrate a novel method for CTC isolation and release using a simple wedge-shaped microfluidic chip embedding degradable znic oxide nanorods (ZnNRs) substrate. By integrating size-dependent filtration with degradable nanostructured substrate, the capture efficiencies over 87.5% were achieved for SKBR3, PC3, HepG2 and A549 cancer cells spiked in healthy blood sample with the flow rate of 100 µL min-1. By dissolving ZnNRs substrate with an extremely low concentration of phosphoric acid (12.5 mM), up to 85.6% of the captured SKBR3 cells were released after reverse injection with flow rate of 100 µL min-1 for 15 min, which exhibited around 73.6% cell viability within 1 h after release to around 93.9% after re-cultured for 3 days. It is conceivable that our microfluidic device has great potentials in carrying on cell-based biomedical studies and guiding individualized treatment in the future.

Radial basis function neural network ensemble for predicting protein-protein interaction sites in heterocomplexes.

Prediction of protein-protein interaction sites can guide the structural elucidation of protein complexes. We propose a novel method using a radial basis function neural network (RBFNN) ensemble model for the prediction of protein interaction sites in heterocomplexes. We classified protein surface residues into interaction sites or non-interaction sites based on the RBFNNs trained on different datasets, then judged a prediction to be the final output. Only information of evolutionary conservation and spatial sequence profile are used in this ensemble predictor to describe the protein sites. A non-redundant data set of heterodimers used is consisted of 69 protein chains, in which 10329 surface residues can be found. The efficiency and the effectiveness of our proposed approach can be validated by a better performance such as the accuracy of 0.689, the sensitivity of 66.6% and the specificity of 67.6%.

Inferring protein-protein interactions using a hybrid genetic algorithm/support vector machine method.

Identifying protein-protein interaction is crucial for understanding the biological systems and processes, as well as mutant design. This paper proposes a novel hybrid Genetic Algorithm/Support Vector Machine (GA/SVM) method to predict the interactions between proteins intermediated by the protein-domain relations. A protein domain is a structural and/or functional unit of the protein. Every protein can be characterized by a distinct domain or a sequential combination of multiple domains. In our method, the protein was first represented by its domains where the effects of domain duplication were also considered. Transformation of the domain composition was taken to simulate the combination of different domains using genetic algorithm (GA). The optimal transformation was discovered using a predictor constructed by a support vector machines (SVM) method. Compared with random predictor, the prediction performance of our method is more effective and efficient with 0.85 sensitivity, 0.90 specificity and 0.88 accuracy.