Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the evolution of nonverbal synchrony in psychotherapy: The idiographic perspective provides a different picture

Abstract Objectives: A methodological obstacle for the assessment of psychotherapy process concerns the compatibility between nomothetic versus idiographic approaches. Using quantitative methodology at an idiographic level, we seek to narrow this gap for the special case of nonverbal synchrony in psychotherapy dyads. Methods: Using quantitative idiographic process analysis (QUIPA), we combined the assessments of nonverbal synchrony—the coordination of patient's and therapist's body-movement—quantified with motion energy analysis (MEA), patient- and therapist session-reports, and patient’s self-reports of symptomatology into multivariate time-series of psychotherapy process across the course of N = 12 dyadic psychotherapies with a total of N = 150 sessions. Adopting both mixed models as well as vector auto regressive models (VAR) to time-series, we aimed to extend previous results assessed in a randomized sample by exploring the evolution of nonverbal synchrony in psychotherapy dyads across time. Results: Aggregated idiographic data revealed that nonverbal synchrony was different from findings based on a previously reported nomothetic account: Associations with session-level outcome were weaker and did not replicate cross-sectional analyses. Conclusions: The application of idiographic assessments may help broadening our conception of synchrony in psychotherapy and also reminds us that ergodicity is not necessarily the usual case, but one of many possibilities.
Life goes on: The influence of the perceived quality of social relations on older women’s mental health after the loss of a partner in Europe

Abstract The loss of a spouse/partner is a major stressor, undermining one’s mental health, especially in mid-life and old age. Social ties are key moderators of the impact of bereavement, serving to enhance psychological resilience and facilitating social engagement and access to resources. Our aim was to explore the association between depression levels and the interaction between the composition of, and level of satisfaction with, social networks among women who have lost their husband. The study was undertaken from a cross-national perspective, examining women throughout Europe. We used data from the SHARE Survey (sixth wave; N = 6,820). Using linear regression models, we find negative evaluations of social relations influenced the mental health of European widows, mostly when relatives exclusively composed their social network. The perceived quality of that network had more impact on the mental health of older widows in Northern and Western European countries than in their Southern and Eastern counterparts.
Assessing precision and requirements of three methods to estimate roe deer density

Roe deer (Capreolus capreolus) is the most abundant cervid in Europe and, as such, has a considerable impact over several human activities. Accurate roe deer population size estimates are useful to ensure their proper management. We tested 3 methods for estimating roe deer abundance (drive counts, pellet-group counts, and camera trapping) during two consecutive years (2012 and 2013) in the Apennines (Italy) in order to assess their precision and applicability. During the study period, population density estimates were: drive counts 21.89±12.74 roe deer/km2 and pellet-group counts 18.74±2.31 roe deer/km2 in 2012; drive counts 19.32±11.12 roe deer/km2 and camera trapping 29.05±7.48 roe deer/km2 in 2013. Precision of the density estimates differed widely among the 3 methods, with coefficients of variation ranging from 12% (pellet-group counts) to 58% (drive counts). Drive counts represented the most demanding method on account of the higher number of operators involved. Pellet-group counts yielded the most precise results and required a smaller number of operators, though the sampling effort was considerable. When compared to the other two methods, camera trapping resulted in an intermediate level of precision and required the lowest sampling effort. We also discussed field protocols of each method, considering that volunteers, rather than technicians, will more likely be appointed for these tasks in the near future. For this reason, we strongly suggest that for each method managers of population density monitoring projects take into account ease of use as well as the quality of the results obtained and the resources required.
A porous collagen‐GAG scaffold promotes muscle regeneration following volumetric muscle loss injury

Volumetric muscle loss (VML) is a segmental loss of skeletal muscle which commonly heals with fibrosis, minimal muscle regeneration, and loss of muscle strength. Treatment options for these wounds which promote functional recovery are currently lacking. This study was designed to investigate whether the collagen‐GAG scaffold (CGS) promotes functional muscle recovery following VML. A total of 66 C57/Bl6 mice were used in a three‐stage experiment. First, 24 animals were split into three groups which underwent sham injury or unilateral quadriceps VML injury with or without CGS implantation. Two weeks post‐surgery, muscle was harvested for histological and gene expression analysis. In the second stage, 18 mice underwent bilateral quadriceps VML injury, followed by weekly functional testing using a treadmill. In the third stage, 24 mice underwent sham or bilateral quadriceps VML injury with or without CGS implantation, with tissue harvested six weeks post‐surgery for histological and gene expression analysis. VML mice treated with CGS demonstrated increased remnant fiber hypertrophy versus both the VML with no CGS and uninjured groups. Both VML groups showed greater muscle fiber hypertrophy than non‐injured muscle. This phenomenon was still evident in the longer‐term experiment. The gene array indicated that the CGS promoted upregulation of factors involved in promoting wound healing and regeneration. In terms of functional improvement, the VML mice treated with CGS ran at higher maximum speeds than VML without CGS. A CGS was shown to enhance muscle hypertrophy in response to VML injury with a resultant improvement in functional performance. A gene array highlighted increased gene expression of multiple growth factors following CGS implantation. This suggests that implantation of a CGS could be a promising treatment for VML wounds.
Real-Time Human-In-The-Loop Simulation with Mobile Agents, Chat Bots, and Crowd Sensing for Smart Cities

Modelling and simulation of social interaction and networks are of high interest in multiple disciplines and fields of application ranging from fundamental social sciences to smart city management. Future smart city infrastructures and management are characterised by adaptive and self-organising control using real-world sensor data. In this work, humans are considered as sensors. Virtual worlds, e.g., simulations and games, are commonly closed and rely on artificial social behaviour and synthetic sensor information generated by the simulator program or using data collected off-line by surveys. In contrast, real worlds have a higher diversity. Agent-based modelling relies on parameterised models. The selection of suitable parameter sets is crucial to match real-world behaviour. In this work, a framework combining agent-based simulation with crowd sensing and social data mining using mobile agents is introduced. The crowd sensing via chat bots creates augmented virtuality and reality by augmenting the simulated worlds with real-world interaction and vice versa. The simulated world interacts with real-world environments, humans, machines, and other virtual worlds in real-time. Among the mining of physical sensors (e.g., temperature, motion, position, and light) of mobile devices like smartphones, mobile agents can perform crowd sensing by participating in question–answer dialogues via a chat blog (provided by smartphone Apps or integrated into WEB pages and social media). Additionally, mobile agents can act as virtual sensors (offering data exchanged with other agents) and create a bridge between virtual and real worlds. The ubiquitous usage of digital social media has relevant impact on social interaction, mobility, and opinion-making, which has to be considered. Three different use-cases demonstrate the suitability of augmented agent-based simulation for social network analysis using parameterised behavioural models and mobile agent-based crowd sensing. This paper gives a rigorous overview and introduction of the challenges and methodologies used to study and control large-scale and complex socio-technical systems using agent-based methods.
Sucrose Synthase Enhances Hull Size and Grain Weight by Regulating Cell Division and Starch Accumulation in Transgenic Rice

Grain size and weight are two important determinants of grain yield in rice. Although overexpression of sucrose synthase (SUS) genes has led to several improvements on cellulose and starch-based traits in transgenic crops, little is reported about SUS enhancement of hull size and grain weight in rice. In this study, we selected transgenic rice plants that overexpressed OsSUS1-6 genes driven with the maize Ubi promoter. Compared to the controls (wild type and empty vector line), all independent OsSUS homozygous transgenic lines exhibited considerably increased grain yield and grain weights. Using the representative OsSUS3 overexpressed transgenic plants, four independent homozygous lines showed much raised cell numbers for larger hull sizes, consistent with their enhanced primary cell wall cellulose biosynthesis and postponed secondary wall synthesis. Accordingly, the OsSUS3 transgenic lines contained much larger endosperm volume and higher starch levels than those of the controls in the mature grains, leading to increased brown grain weights by 15–19%. Hence, the results have demonstrated that OsSUS overexpression could significantly improve hull size and grain weight by dynamically regulating cell division and starch accumulation in the transgenic rice.
Hijacking intracellular membranes to feed autophagosomal growth

Autophagy is widely considered as a housekeeping mechanism that enables cells to survive stress conditions and, in particular, nutrient deprivation. Autophagy begins with the formation of the phagophore that expands and closes around cytosolic material and damaged organelles destined for degradation. The execution of this complex machinery is guaranteed by the coordinated action of more than 40 ATG (autophagy‐related) proteins that control the entire process at different stages from the biogenesis of the autophagosome to cargo sequestration and fusion with lysosomes. Autophagosome biogenesis occurs at multiple intracellular sites, such as the endoplasmic reticulum (ER) and the plasma membrane. Soon after the formation of the phagophore, the nascent autophagosome progressively grows in size and ultimately closes by recruiting intracellular membranes. In this review, we focus on the contribution of three membrane sources – the ER, the ER–Golgi intermediate compartment, and the Golgi complex – to autophagosome biogenesis and expansion. We also highlight the interplay between the secretory pathway and autophagy in cells when nutrients are scarce.
APOL1-Associated Collapsing Focal Segmental Glomerulosclerosis in a Patient With Stimulator of Interferon Genes (STING)-Associated Vasculopathy With Onset in Infancy (SAVI)

Apolipoprotein L1 (APOL1) risk variants G1 and G2 are known to result in risk for kidney disease in patients of African ancestry. APOL1-associated nephropathy typically occurs in association with certain environmental factors or systemic diseases. As such, there has been increasing evidence of the role of interferon (IFN) pathways in the pathogenesis of APOL1-associated collapsing glomerulopathy in patients with human immunodeficiency virus (HIV) infection and systemic lupus erythematosus, 2 conditions that are associated with high IFN levels. Collapsing glomerulopathy has also been described in patients receiving exogenous IFN therapy administered for various medical conditions. We describe a patient with a genetic condition that results in an increased IFN state, stimulator of IFN genes (STING)-associated vasculopathy with onset in infancy (SAVI), who developed collapsing glomerulopathy during a flare of his disease. The patient was found to have APOL1 G1 and G2 risk variants. This case supports the role of IFN in inducing APOL1-associated collapsing glomerulopathy.
Place recognition based visual localization in changing environments

In many applications, it is crucial that a robot or vehicle localizes itself within the world especially for autonomous navigation and driving. The goal of this thesis is to improve place recognition performance for visual localization in changing environment. The approach is as follows: in off-line phase, geo-referenced images of each location are acquired, features are extracted and saved. While in the on-line phase, the vehicle localizes itself by identifying a previously-visited location through image or sequence retrieving. However, visual localization is challenging due to drastic appearance and illumination changes caused by weather conditions or seasonal changing. This thesis addresses the challenge of improving place recognition techniques through strengthen the ability of place describing and recognizing. Several approaches are proposed in this thesis:1) Multi-feature combination of CSLBP (extracted from gray-scale image and disparity map) and HOG features is used for visual localization. By taking the advantages of depth, texture and shape information, visual recognition performance can be improved. In addition, local sensitive hashing method (LSH) is used to speed up the process of place recognition;2) Visual localization across seasons is proposed based on sequence matching and feature combination of GIST and CSLBP. Matching places by considering sequences and feature combination denotes high robustness to extreme perceptual changes;3) All-environment visual localization is proposed based on automatic learned Convolutional Network (ConvNet) features and localized sequence matching. To speed up the computational efficiency, LSH is taken to achieve real-time visual localization with minimal accuracy degradation.
A Priority-Based Interactive Model for a Microgrid Cluster and the Distribution Network

This paper proposes a new energy management framework for the coordinated operation of a microgrid cluster and the distribution network. Each microgrid not only schedules its local power generation and load consumption, but also trades energy with neighbouring microgrids in the distribution network, thereby, alleviating the demand and reliance on the distribution grid. Within this framework, a contribution-based prioritizing scheme is embodied in order to coordinate the power exchanges between microgrids. Through the prioritizing scheme, microgrids are rewarded in the form of priority for their active participation in the coalition. Microgrids are thereby, modelled as autonomous entities that aim at minimizing their own operating costs and gain benefits through energy trading. Various system intermittencies are captured using the scenario generation and reduction processes. Results prove the effectiveness of the proposed approach in achieving a significant reduction in the network power losses, operating costs, voltage fluctuations and storage capacity requirements of microgrids.
EEG-Hat with Candle-like Microneedle Electrode

This paper reports the EEG-Hat, the hat-type EEG device with candle-like dry microneedle electrodes. Current wearable EEG devices have two major problems; 1) no adjustability to every participant and 2) no ability to measure EEG at hairy part. If these problems are solved, health care technologies in daily life will be developed drastically. The EEG-Hat potentially solves these problems. This device can adjust the electrodes to different size and shape of human head. This device has shutter-like structures to separate hair, so using this device, it is possible to measure EEG without separating hair by hand. First, we quantified the force to press the electrodes and the amount of separating hair. Then, the EEG-Hat fabricated based on the findings successfully measured EEG from 3 hairy parts without manual separation.
Frequency and Phase Synchronization in Distributed (Implantable-Transcutaneous) Neural Interfaces

Synchronized oscillations are a ubiquitous feature of neuronal circuits and can modulate online information transfer and plasticity between brain areas. The disruption of these oscillatory processes is associated with the symptoms of several brain disorders. While conventional therapeutic high-frequency deep brain stimulation can perturb neuronal oscillations, manipulating the timing of oscillatory activity between areas more precisely could provide a more efficient and effective method of modulating these activities. Here we describe a prototype circuit for synchronizing the clocks between an active implantable and an external sensing and stimulation system that could be used to achieve this goal. Our specific focus is on synchronizing the systems for paired-associative stimulation. The ability to repetitively drive two brain regions with a fixed latency has specific implications for neural plasticity. Furthermore, the general concept can be applied for many potential applications involving distributed neural interfaces.
Parameter Estimation of Photovoltaic System Using Real Condition Data

Phovoltaic generation have been increasing around the world as an important alternative of energy production. Therefore, studies to foresee the impact of inclusion of this type of energy in the network become necessary. For this goal, the representation of these photovoltaic generators by equivalent model and the estimation of its parameter is an important area to study. Usually manufactures of photovoltaic modules provide some information to obtain model parameters of those panels using standard test conditions. However, in real situation, rarely those conditions are similar of those where the photovoltaic modules are installed. In this research a method for parameter estimation of equivalent photovoltaic power plant model is proposed using real measuremets. The improved single diode model was select to represent the photovoltaic system and the mean-variance mapping optimization method was used to estimate the parameters. A comparison between the parameter estimated with standard test condition and with real measurements was performed in a real photovoltaic system installed in Sao Paulo University. The results have shown differences between parameters estimated with real measurement compared with stander test condition, especially a parallel and series resistances.
Safe Traffic Sign Recognition through Data Augmentation for Autonomous Vehicles Software

Context: Since autonomous vehicles operate in an open context, their software components, including data-driven ones, have to reliably process inputs (e.g., obtained by cameras) in order to make safe decisions. A key challenge when providing reliable data-driven components is insufficient training data, which could lead to wrong interpretation of the environment, thereby causing accidents. Aim: The goal of our research is to extend available training data of data-driven components for safe autonomous vehicles using the example of traffic sign recognition. Method: We developed an approach to create realistic image augmentations of various quality deficits and applied them on the German traffic sign recognition benchmark dataset (GTSRB). Results: The approach results in images augmented with (any combination of) seven different quality deficits affecting traffic sign recognition (rain, dirt on lens, steam on lens, darkness, motion blur, dirt on sign, backlight) and considers dependencies between combined quality deficits and influences from other contextual information. Conclusion: Our approach can be used to obtain more comprehensive datasets, especially also including samples with quality deficits that are difficult to gather. By structuring the augmentation into a set of basic components, the approach can be adapted for other application domains (e.g., person detection).
Overheating decomposition characteristics of epoxy dielectrics in SF6 atmosphere

In this paper, the thermal decomposition characteristics of epoxy resin in SF<inf>6</inf> was studied using simultaneous thermal analysis (TG/DSC) and gas chromatograph-mass spectrometry (GC-MS). The concentrations of the decomposed gas components were tested, and the method of determining whether the failure of SF<inf>6</inf> gas insulation equipment is caused by thermal decomposition of the insulating epoxy resin material is proposed. TG-DSC shows that the epoxy resin starts to lose weight sharply at 350 °C, and heating from 350 to 450 °C shows that the main gas products are CO<inf>2</inf>, SO<inf>2</inf>, H<inf>2</inf>S and SOF<inf>2</inf>. The concentrations of the four gases are significantly higher than where no epoxy resin is present and only pure SF<inf>6</inf> is injected. The concentrations of SO<inf>2</inf>F<inf>2</inf>, CF<inf>4</inf> and CS<inf>2</inf> were all kept below 0.5 ppm in the given temperature range. H<inf>2</inf>S is generated at about 325 °C while it can hardly be detected in the decomposition products of pure SF<inf>6</inf> without epoxy resin at the same temperature. Based on our observations, it is concluded that when the concentration of CO<inf>2</inf> reaches 5 times the sum of the concentrations of SO<inf>2</inf> and H<inf>2</inf>S, and when the concentration of H<inf>2</inf>S is higher than 0.5 ppm, failure of electrical equipment occurs by thermal decomposition of epoxy resin will occur.
The relation of skin conductance and pupillary fluctuations assessed by phase-rectified signal averaging

The reaction of pupil diameter and skin conductance are widely studied marker of the autonomic response to arousing stimuli. However, little is known about their relation at rest.In this study, we used bivariate phase-rectified signal averaging to investigate the relationship of skin conductance fluctuations (SCF) and pupillary fluctuations in 83 healthy volunteers. The onset of each SCF was detected by a pattern matching algorithm. Those time points were corrected for a different neurotransmission delay. Cross-correlation of temporal derivatives of pupil diameter and skin conductance revealed an average time lag of 2.5s. Thus, anchor points 2.5s before an SCF were defined. The pupillary signal following these anchors (7s) were extracted and normalized to baseline 1s prior to the anchor point. Aligned segments were averaged to determine the amplitude and area under the curve (AUC) of characteristic pupil diameter fluctuations (PDF) concurrent to SCF. The same procedure was applied to random time points (non-SCF) with at least 1s distance to actually detected SCF which served as control condition.SCF were accompanied by increases of pupil diameter with a maximum dilation of 9% on average. The one sample t-test indicated an AUC of PDF (70 ± 110 n.u., p<0.001). The maximum change and AUC of pupillary reactions were significantly higher when PDF extraction was triggered by actual SCF (both p<0.001). Both measures of pupillary dilations contributed significantly to pupillary unrest.Our results suggest that sympathetic arousal as detected by skin conductance fluctuations is accompanied by pupil dilation.