Miracle-dz/UniFAR-FTUs huggingface dataset:
Neurophysiological changes associated with vibroacoustically-augmented breath-focused mindfulness for dissociation: targeting interoception and attention

Background Dissociative symptoms can emerge after trauma and interfere with attentional control and interoception, both of which are barriers to mind-body interventions such as breath-focused mindfulness (BFM). To overcome these barriers, we tested the use of an exteroceptive augmentation to BFM, using vibrations equivalent to the amplitude of the auditory waveform of the actual breath, delivered via a wearable subwoofer in real time (VBFM). We tested whether this device enhanced interoceptive processes, attentional control and autonomic regulation in trauma-exposed women with dissociative symptoms. Method 65 women, majority (82%) Black American, aged 18-65 completed self-report measures of interoception and 6 BFM sessions, during which electrocardiographic recordings were taken to derive high-frequency heart rate variability (HRV) estimates. A subset (n=31) of participants completed functional MRI at pre- and post-intervention, during which they were administered an affective attentional control task. Results Compared to those who received BFM only, women who received VBFM demonstrated greater increases in interoception, particularly their ability to trust body signals, increased sustained attention, and as well as increased connectivity between nodes of emotion processing and interoceptive networks. Intervention condition moderated the relationship between interoception change and dissociation change, as well as the relationship between dissociation and HRV change. Conclusions Vibration feedback during breath focus yielded greater improvements in interoception, sustained attention and increased connectivity of emotion processing and interoceptive networks. Augmenting BFM with vibration appears to have considerable effects on interoception, attention and autonomic regulation; it could be used as a monotherapy or to address trauma treatment barriers.
SCAR and the Arp2/3 complex polarise the actomyosin cortex and plasma membrane organization in asymmetrically dividing neuroblasts

While the Formin-nucleated actomyosin cortex has been shown to drive the changes in cell shape that accompany cell division in both symmetric and asymmetric cell divisions, it is not clear whether or not Arp2/3-nucleated branched actin filament networks also play a role. In order to look for mitotic roles of the Arp2/3 complex, here we use Drosophila neural stem cells as a model system. These cells are unusual in that they divide asymmetrically to produce a large and small daughter cell with different fates. Our analysis identifies a pool of Arp2/3-dependent actin-based membrane protrusions that form at the apical cortex of these cells as they enter mitosis. Strikingly, at metaphase, these protrusions co-localise with components of the SCAR complex. By perturbing Arp2/3 complex activity we show that this apical pool of actin likely functions to limit the accumulation of apical Myosin in metaphase. Following the onset of anaphase, the loss of these SCAR and Arp2/3 dependent structures then leads to a delay in the clearance of apical Myosin and to cortical instability at cytokinesis. These data point to a role for a polarised branched actin filament network in fine tuning the apical actomyosin cortex to enable the precise control of cell shape during asymmetric cell division.
3D genome organization around nuclear speckles drives mRNA splicing efficiency

The nucleus is highly organized such that factors involved in transcription and processing of distinct classes of RNA are organized within specific nuclear bodies. One such nuclear body is the nuclear speckle, which is defined by high concentrations of protein and non-coding RNA regulators of pre-mRNA splicing. What functional role, if any, speckles might play in the process of mRNA splicing remains unknown. Here we show that genes localized near nuclear speckles display higher spliceosome concentrations, increased spliceosome binding to their pre-mRNAs, and higher co-transcriptional splicing levels relative to genes that are located farther from nuclear speckles. We show that directed recruitment of a pre-mRNA to nuclear speckles is sufficient to drive increased mRNA splicing levels. Finally, we show that gene organization around nuclear speckles is highly dynamic with differential localization between cell types corresponding to differences in Pol II occupancy. Together, our results integrate the longstanding observations of nuclear speckles with the biochemistry of mRNA splicing and demonstrate a critical role for dynamic 3D spatial organization of genomic DNA in driving spliceosome concentrations and controlling the efficiency of mRNA splicing
A phosphorylation switch regulates RAB6 function during mitosis

RAB GTPases are key regulators of membrane trafficking in eukaryotic cells. In addition to their role in interphase, several RAB proteins, including Golgi-associated RAB6, have mitotic functions. The aim of this study was to investigate how the interphasic and mitotic functions of RAB6 could be regulated. Since phosphorylation is a key regulatory process in mitosis, we looked for specific mitotic phosphorylation of RAB6 using a phospho-proteomic approach. We found that RAB6 is phosphorylated at position S52 by the mitotic kinase Pololike kinase 1 (Plk1) in mitosis. Phosphorylated RAB6 localizes at the spindle poles from prophase to anaphase. In metaphase, we observed RAB6A-positive structures containing Mad1 and Mad2 moving along the mitotic spindle via the dynein-dynactin complex. We provide evidence that phosphorylation impairs RAB6A binding to some of its known partners, including p150Glued and Bicaudal-D2. In addition, the overexpression of RAB6A phospho-mutants lead to mitosis and cytokinesis defects. Our results suggest that a cycle of RAB6 phosphorylation/dephosphorylation is required for cell division.
The “replacing surgery” of cpDNA: de novo chemical synthesis and in vivo functional testing of Chlamydomonas chloroplast genome

We have successfully designed and synthesized the 221,372-bp cpDNA SynCpV1.0 with the native cpDNA of Chlamydomonas reinhardtii as the template. Homoplasmic SynCpv1.0-harboring algal strains were obtained by biolistic transformation and selected with an ascending gradient of antibiotic pressure. Meanwhile, we were pleasantly surprised to find that SynCpV1.0 was able to re-introduce and replicate normally after the total DNA of transplastomic algal strains were transformed to Escherichia coli, it indicated that SynCpV1.0 was able to shuttle between C. reinhardtii and E. coli. Finally, we analyzed the photosynthetic properties of SynCpV1.0-harboring transplastomic strains, the results showed that they exhibited the same photosynthetic efficiency as the wild strain of C. reinhardtii CC125, and could rescue the photosynthetic defect in mutant strain of C. reinhardtii CC5168. Herein, we have performed the “replacing surgery” of cpDNA and established an ideal platform to complete multiple cycles of “Design-Build-Test” for optimizing the cpDNA of photosynthetic organisms. Highlight An artificial cpDNA SynCpV1.0 is constructed by de novo chemical synthesis. The “replacing surgery” of cpDNA was performed in the chloroplast of C. reinhardtii It is found that artificial cpDNA was able to shuttle between Chlamydomonas chloroplast and E. coli. Establish an ideal platform to complete multiple cycles of “Design-Build-Test” for optimizing the cpDNA. One-Sentence Summary The chloroplast genome can be replaced by a complete synthesized genome and performs the designed biological function in C. reinhardtii.
Point mutations in the catalytic domain disrupt cellulose synthase (CESA6) vesicle trafficking and protein dynamics

Cellulose, as the main component of the plant cell wall, is synthesized by a multimeric protein complex named the cellulose synthase (CESA) complex or CSC. In plant cells, CSCs are transported through the endomembrane system to the PM, but how catalytic activity or conserved motifs around the catalytic core domain influence vesicle trafficking or protein dynamics is not well understood. Here, we used a functional YFP-tagged AtCESA6 and site- directed mutagenesis to create 18 single amino acid replacement mutants in key motifs of the catalytic domain including DDG, DXD, TED and QXXRW, to comprehensively analyze how catalytic activity affects plant growth, cellulose biosynthesis, complex formation, as well as CSC dynamics and trafficking. Plant growth and cellulose content were reduced by nearly all mutations. Moreover, mutations in most conserved motifs reduced the speed of CSC movement in the PM as well as delivery of CSCs to the PM. Interestingly, the abundance of YFP-CESA6 in the Golgi apparatus was increased or reduced by mutations in DDG and QXXRW motifs, respectively. Post-Golgi trafficking of CSCs was also differentially perturbed by these mutations and, based on these phenotypes, the 18 mutations could be divided into two major groups. Group I comprises mutations causing significantly increased fluorescence intensity of YFP-CESA6 in Golgi with either an increase or no change in the abundance of cortical small CESA-containing compartments (SmaCCs). In contrast, Group II represents mutations with significantly decreased fluorescence intensity of YFP-CESA6 in Golgi and/or reduced SmaCC density. In addition, two Group II mutations in the QXXRW motif reduced CSC assembly in the Golgi. We propose that Group I mutations cause CSC trafficking defects whereas Group II mutations, especially in the QXXRW motif, affect normal CSC rosette formation in the ER or Golgi and hence interfere with subsequent CSC trafficking. Collectively, our results demonstrate that the catalytic domain of CESA6 is essential not only for cellulose biosynthesis, but also CESA complex formation, protein folding and dynamics, vesicle trafficking, or all of the above. One sentence summary A comprehensive mutational analysis of the catalytic domain of Arabidopsis CESA6 reveals distinct roles for conserved motifs in CSC vesicle trafficking, protein complex formation, or protein dynamics
Particle-filter-based detection schemes

The problem of detecting whether or not a signal is present is often encountered. Several detection strategies lead to a likelihood ratio test against a threshold. In a simple setting explicit expressions for the likelihood can be obtained. However when the signal to be detected is generated by a nonlinear, non-Gaussian dynamical system it is in general impossible to obtain an expression for the probability of the signal under the hypothesis that it is present. Recently, so called particle filters have been proposed to solve nonlinear, non-Gaussian filtering problems. In this paper we show that the filtering solution obtained by a particle filter can be used to construct the likelihood ratio, needed to perform the likelihood ratio test for detection. Here we will show that different detection schemes can be used. These schemes have in common that they use the output of a particle filter for the purpose of detecting the possible presence of a target. Furthermore we will go into aspects that are of importance when actually building such a particle filter based detector.
Agricultural Machines and Internet of Things

The Internet of Things (IoT) is revolutionizing the world at an alarming rate. The connection between things offered by internet is changing the way day-to-day things are perceived. Agriculture is one such sector which cannot be left untouched by this technological development. In this paper, we focus on the impact of IoT on agricultural machines with our primary focus on hydraulic systems and how it will affect the productivity. Hydraulic system's performance is highly affected by the hydraulic oil temperatures. The performance is way below average if the hydraulic oil is not at the optimum temperature. This is especially true in case of regions with low temperatures for most part of the year. In one such case, if the hydraulic oil temperature is low then the values acquired by different routines like the calibrations are inaccurate. The performance of such system depends on the calibrated values and will under-perform due to incorrect parameters. These issues can be addressed using IoT and connected machines. In case of agricultural equipment, there are multiple machines operating on the fields having similar hydraulic systems. On these machines, calibrations can be performed on the go when affecting factors like the hydraulic oil have heated up to optimum temperature. The runtime performance data can then be collected from these machines and analyzed for the best combinations of calibration parameters. These parameters will help in assisting each hydraulic system to operate at its optimum performance as compared to the system that runs using inaccurate parameters. Lastly, we will also address the challenges in implementation of the proposed idea with respect to existing infrastructure, data security and maintenance.
What can we learn from a deep dive into transformer oil analysis data

Transformer monitoring is the measurement, collection, and careful analysis of all relevant data regarding an electric transformer. If we measure the right data in real time and learn how to interpret this data, a good insight into the working condition of a transformer can be delivered. Constant monitoring results then in either required and immediate maintenance or can provide more maintenance-free time.
Modelling and controller design for a five-link inverted pendulum

The inverted pendulum is a fast-moving, highly nonlinear and unstable system with multiple variables and non-minimum phase that requires effective stabilization controllers. Therefore, studies into inverted pendulum systems theoretically and practically have great significance. The Euler-Lagrange Equation is used to calculate the mathematical model for a five-link inverted pendulum system. Linear Quadratic Gaussian (LQG) and $\mathcal{H}_{\infty}$ are implemented using the developed model, with the Kalman Filter serving as the observer. The closed-loop system are simulated by the Matlab-Simscape platform and the controller are evaluated in relation to the system performance.
Fuel Cell Ageing Prediction and Remaining Useful Life Forecasting

Fuel cell (FC) lifetime prediction is becoming an integral part of any energy management strategy (EMS) in electrified vehicles since it is one of the key barriers in the commercialization of FCs. Remaining useful life (RuL) estimation is one of the most effective predictive maintenance tools used to develop EMSs. Prognostic health management (PHM) techniques can track the degradation of a FC and predict its RuL. Hence, in this paper, a data-based PHM method based on Long Short-Term Memory Network (LSTM) is proposed to predict the RuL of FC. This manuscript presents a benchmark to compare the prediction of the FC voltage degradation with other works that have used the same dataset. The results indicate an accuracy of 88.13% with RMSE of 0.0079, and RuL is forecasted for 135 hours of operation with an accuracy of 92.5%. Furthermore, LSTM is used to predict ageing trend of FC by considering a different current profile that the network has been trained with. This generalization has an accuracy of 79.99%. with an RMSE of 0.0351.
Avatar-Darwin a Social Humanoid with Telepresence Abilities Aimed at Embodied Avatar Systems

Human compassion has driven the creation of social robots that provide aid and interactions to people in need. However, such systems are preprogrammed and are therefore asocial as they lack adaptability and authenticity in their interactions. In this paper, the miniature biped DARwIn-OP was upgraded into Avatar-DARwIn, a humanoid telepresence platform that broadcasts human cognition. To address a body correspondence problem related to miniature humanoid embodiment, a “Marionette Method” of scaling was developed. Furthermore, results have shown that operator motions were successfully retargeted to Avatar-DARwIn, allowing operators to complete an array of social tasks. Additionally, a System Usability Scale (SUS) Test was administered amongst a pool of eleven participants to evaluate operator experience and system functionality. Data collected from SUS testing (based on a 5-point LIKERT scale) found that operators felt a high sense of telepresence as this category received a score of 4.36. Overall, this teleoperated, real-time telepresence system allows human operators to embody a miniature social humanoid to connect people around the world, regardless of distance.
Region-based method for passive millimeter-wave imaging detection

Passive millimeter-wave (PMMW) imaging is a powerful approach for detecting concealed objects underneath clothing. Object detection is an important issue in personnel security inspection. Much previous research has been carried out based on the gray-scale image of brightness temperature. Existing methods are mainly based on single-pixel processing. In this paper, we present a region-based method for concealed object detection. By combining superpixel segmentation and Fisher vectors, a new indicator, regional Fisher vector (RFV), is used to generate binary detection. Several imaging data of a typical personnel security inspection scenario are used to verify the proposed method.
Enhancing a Biological inspired Self-organized Architecture towards Smart Manufacturing

In last decades, new manufacturing requirements have introduced new approaches for distributed control and automation, some of them introducing concepts as self-organization and emergence. BIOSOARM (a Bio-inspired Self-organising Architecture for Manufacturing Cyber-physical Shopfloors) is an example of such architectures. It has significant insights regarding self-organization, pluggability and scalability of manufacturing resources. Despite such architectural patterns, there are aspects that can be integrated and enhanced e.g. the utilization of experience-based knowledge, stability mechanisms, process optimization, etc. These aspects are also part of current industrial expectations and can improve its adaptability and evolvability. Thus, the major contribution of this paper is to have a path and discussion towards enhancing BIOSOARM by means of a weaknesses analysis. As a result, new building blocks to the existing BIOSOARM architecture are proposed. The matrix production concept is suggested as a potential use case of the current approach.
Online Human Intention Detection through Machine-learning based Algorithm for the Control of Lower-limbs Wearable Robot

Online human intention detection is one of the main challenges to ensure smooth human robot interaction for assistive robotics through wearable devices. This paper proposes a framework that combines both machine learning based algorithms and task-oriented control of an actuated-ankle-foot orthosis for human locomotion assistance during five gait modes that are level walking, stairs ascent/descent, and ramp ascent/descent. A random-forest based algorithm has been trained to provide an online classification of the five gait modes using kinematic features of a dataset collected with ten healthy subjects. Finally, appropriate assistive torques were applied at the ankle joint level with respect to the detected gait mode. The proposed scheme is verified in terms of gait mode detection success rate and the torque assistance through the actuated-ankle-foot orthosis at the ankle joint level. One healthy subject participated in the experiments with and without applying the torque assistance strategy. The results show the following average success rates of 99.49%, 98.30%, 96.07%, 84.63%, and 85.55% for the different locomotion modes, that are level walking, stair ascent, stair descent, ramp ascent, and ramp descent, respectively.
Volatility Integration of Gold and Copper with Foreign Exchange Rates

Copper and Gold today are some of the key metals in the metals and mining space especially due to the external events happening such as Covid-19 pandemic and Russia-Ukraine war. Also, the rupee-dollar exchange rate is highly volatile currently. The study's goal is to determine how copper and crude oil's shock volatility and price volatility affect the exchange rates between the rupee and the dollar. The study tries to find the correlation and mutual association between the metals (copper prices and gold prices) and foreign exchange rate. In order to establish such a relationship, bi-variate GARCH models (VEC GARCH and BEKK GARCH) are applied to sample data of the copper price, gold price, and foreign exchange rate (rupee-dollar) taken from the period 2005 to 2020 to determine a mutual correlation and volatility spillover effect in the metals and forex markets.
Correcting winds measured with a Rayleigh Doppler lidar from pressure and temperature effects

The molecular channel of the space-based Doppler lidar ADM-Aeolus relies on a double Fabry—Perot (FP) interferometer. The difference in photon numbers transmitted by the two FPs divided by their sum- the so-called Rayleigh response—is a function of the central frequency of the spectrum of the laser light backscattered by the atmosphere, so that a proper inversion enables the measurement of Doppler shifts and line-of-sight wind velocities. In this paper, it is shown that the relation-ship between the Rayleigh response and the Doppler shift does not depend on the sole characteristics of the instrument, but also on the atmospheric pressure and temperature (through the Rayleigh—Brillouin effect), and the likely presence of a narrow-band radiation due to particle scattering. The impact of these on the precision of inverted Doppler shifts (or line-of-sight winds) is assessed showing that a correction is needed. As they are lacking the appropriate precision, climatology profiles of pressure, temperature or aerosols cannot be used as an input. It is proposed to use data predicted by a numerical weather prediction system instead. A possible correction scheme is proposed. Its implication on the quality of retrieved Rayleigh winds is discussed.
A Terahertz On-Chip Antenna for Intra-chip Wireless Communications

Fast development of multi-core processors relies on integrated data networks for cores to exchange data. With the number of cores ever increasing, the performance of these intra-chip networks becomes a bottleneck that limits the overall performance of a multi-core processor. Fortunately, the use of wireless interconnects can address this issue, especially the terahertz (THz) frequency band can significantly increase the data transmission rates among the cores. This paper presents the planar on-chip antenna (OCA) featuring the Substrate Integrated Waveguide (SIW) and Metamaterials (MTM) technologies for intra-chip wireless interconnects. To increase the bandwidth and the effective area of the radiating surface, $2 \times 2$ circular patches are interconnected diagonally on the top layer with further plus-shaped etching. The proposed OCA consists of three layers, copper-polyimide-copper with an area of $400 \times 400 \mu m^{2}$. S-parameter, voltage standing wave ratio (VSWR), and radiation plots are simulated in ANSYS HFSS. Results show that the proposed OCA is promising for intra-chip wireless communications.