Miracle-dz/UniFAR-FTUs huggingface dataset:
Grasping Weber’s Law in a Virtual Environment: The Effect of Haptic Feedback

Recent findings suggest that the functional separation between vision-for-action and vision-for-perception does not generalize to situations in which virtual objects are used as targets. For instance, unlike actions toward real objects that violate Weber’s law, a basic law of visual perception, actions toward virtual objects presented on flat-screens, or in remote virtual environments, obey to Weber’s law. These results suggest that actions in virtual environments are performed in an inefficient manner and are subjected to perceptual effects. It is unclear, however, whether this inefficiency reflects extensive variation in the way in which visual information is processed in virtual environments or more local aspects related to the settings of the virtual environment. In the current study, we focused on grasping performance in a state-of-the-art virtual reality system that provides an accurate representation of the 3D space. Within this environment, we tested the effect of haptic feedback on grasping trajectories. Participants were asked to perform bimanual grasping movements toward the edges of virtual targets. In the haptic feedback condition, physical stimuli of matching dimensions were embedded in the virtual environment. Haptic feedback was not provided in the no-feedback condition. The results showed that grasping trajectories in the feedback, but not in the no-feedback condition, could be performed more efficiently, and evade the influence of Weber’s law. These findings are discussed in relevance to previous literature on 2D and 3D grasping.
Spinal Manipulative Therapy Alters Brain Activity in Patients With Chronic Low Back Pain: A Longitudinal Brain fMRI Study

Background: Spinal manipulative therapy (SMT) helps to reduce chronic low back pain (cLBP). However, the underlying mechanism of pain relief and the neurological response to SMT remains unclear. We utilized brain functional magnetic resonance imaging (fMRI) upon the application of a real-time spot pressure mechanical stimulus to assess the effects of SMT on patients with cLBP. Methods: Patients with cLBP (Group 1, n = 14) and age-matched healthy controls without cLBP (Group 2, n = 20) were prospectively enrolled. Brain fMRI was performed for Group 1 at three time points: before SMT (TP1), after the first SMT session (TP2), and after the sixth SMT session (TP3). The healthy controls (Group 2) did not receive SMT and underwent only one fMRI scan. During fMRI scanning, a real-time spot pressure mechanical stimulus was applied to the low back area of all participants. Participants in Group 1 completed clinical questionnaires assessing pain and quality of life using a visual analog scale (VAS) and the Chinese Short Form Oswestry Disability Index (C-SFODI), respectively. Results: Before SMT (TP1), there were no significant differences in brain activity between Group 1 and Group 2. After the first SMT session (TP2), Group 1 showed significantly greater brain activity in the right parahippocampal gyrus, right dorsolateral prefrontal cortex, and left precuneus compared to Group 2 (P < 0.05). After the sixth SMT session (TP3), Group 1 showed significantly greater brain activity in the posterior cingulate gyrus and right inferior frontal gyrus compared to Group 2 (P < 0.05). After both the first and sixth SMT sessions (TP2 and TP3), Group 1 had significantly lower VAS pain scores and C-SFODI scores than at TP1 (P < 0.001). Conclusion: We observed alterations in brain activity in regions of the default mode network in patients with cLBP after SMT. These findings suggest the potential utility of the default mode network as a neuroimaging biomarker for pain management in patients with cLBP. Clinical Trial Registration: Chinese Clinical Trial Registry, identifier ChiCTR1800015620.
Extracellular Vesicles as Mediators of Environmental and Metabolic Stress Coping Mechanisms During Mammalian Follicular Development

Extracellular vesicles are evolutionarily conserved nano-sized phospholipid membraned structures and released from virtually all types of cells into the extracellular space. Their ability to carry various molecular cargos (mRNA, miRNA, proteins, and lipids) from one cell to the other to exert functional impact on the target cells enables them to play a significant role in cell to cell communication during follicular development. As the molecular signals carried by extracellular vesicles reflect the physiological status of the cells of origin, they are expected to mediate any effect of environmental or metabolic stress on the follicualr cells and the growing oocyte. Recent studies have evidenced that reproductive cells exposed to various environmental stressors (heat and oxidative stress) released extracellular vesicles enriched with mRNA and miRNA associated with stress response mechanisms. Moreover, the metabolic status of post-calving cows could be well-reflected in the follicular extracellular vesicle's miRNA profile, which signified the potential role of extracellular cellular vesicle molecular signals in mediating the effect of metabolic stress on follicular and oocyte development. In the present review, the potential role of extracellular vesicles in mediating the effect of environmental and metabolic stress in various reproductive cells and oocytes are thoroughly discussed Moreover, considering the importance of extracellular vesicles in shuttling protective or rescuing molecular signals during stress, their potential usage as means of targeted delivery of molecules to mitigate the effect of stress on oocytes are addressed as the focus of future research.
The Lavic Lake Fault: A Long-Term Cumulative Slip Analysis via Combined Field Work and Thermal Infrared Hyperspectral Airborne Remote Sensing

The 1999 Hector Mine earthquake ruptured to the surface in eastern California, with >5 m peak right-lateral slip on the Lavic Lake fault. The cumulative offset and geologic slip rate of this fault are not well defined, which inhibits tectonic reconstructions and risk assessment of the Eastern California Shear Zone (ECSZ). With thermal infrared hyperspectral airborne imagery, field data, and auxiliary information from legacy geologic maps, we created lithologic maps of the area using supervised and unsupervised classifications of the remote sensing imagery. We optimized a data processing sequence for supervised classifications, resulting in lithologic maps over a test area with an overall accuracy of 71 ± 1% with respect to ground-truth geologic mapping. Using all of the data and maps, we identified offset bedrock features that yield piercing points along the main Lavic Lake fault and indicate a 1036 +27/−26 m net slip, with 1008 +14/−17 m horizontal and 241 +51/−47 m vertical components. For the contribution from distributed shear, modern off-fault deformation values from another study imply a larger horizontal slip component of 1276 +18/−22 m. Within the constraints, we estimate a geologic slip rate of <4 mm/yr, which does not increase the sum geologic Mojave ECSZ rate to current geodetic values. Our result supports previous suggestions that transient tectonic activity in this area may be responsible for the discrepancy between long-term geologic and present-day geodetic rates.
A Combined Machine Learning and Residual Analysis Approach for Improved Retrieval of Shallow Bathymetry from Hyperspectral Imagery and Sparse Ground Truth Data

Mapping shallow bathymetry by means of optical remote sensing has been a challenging task of growing interest in recent years. Particularly, many studies exploit earlier empirical models together with the latest multispectral satellite imagery (e.g., Sentinel 2, Landsat 8). However, in these studies, the accuracy of resulting bathymetry is (a) limited for deeper waters (>15 m) and/or (b) is being influenced by seafloor type albedo. This study explores further the capabilities of hyperspectral satellite imagery (Hyperion), which provides several spectral bands in the visible spectrum, along with existing reference bathymetry. Bathymetry predictors are created by applying the semi-empirical approach of band ratios on hyperspectral imagery. Then, these predictors are fed to machine learning regression algorithms for predicting bathymetry. Algorithm performance is being further compared to bathymetry predictions from multiple linear regression analysis. Following the initial predictions, the residual bathymetry values are interpolated by applying the Ordinary Kriging method. Then, the predicted bathymetry from all three algorithms along with their associated residual grids is used as predictors at a second processing stage. Validation results show that by using a second stage of processing, the root-mean-square error values of predicted bathymetry is being improved by ≈1 m even for deeper water (up to 25 m). It is suggested that this approach is suitable for (a) contributing wide-scale, high-resolution shallow bathymetry toward the goals of the Seabed 2030 program and (b) as a coarse resolution alternative to effort-consuming single-beam sonar or costly airborne bathymetric laser surveying.
Vertical Accuracy of Freely Available Global Digital Elevation Models (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM)

Freely available global digital elevation models (DEMs) are important inputs for many research fields and applications. During the last decade, several global DEMs have been released based on satellite data. ASTER and SRTM are the most widely used DEMs, but the more recently released, AW3D30, TanDEM-X and MERIT, are being increasingly used. Many researchers have studied the quality of these DEM products in recent years. However, there has been no comprehensive and systematic evaluation of their quality over areas with variable topography and land cover conditions. To provide this comparison, we examined the accuracy of six freely available global DEMs (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM) in four geographic regions with different topographic and land use conditions. We used local high-precision elevation models (Light Detection and Ranging (LiDAR), Pleiades-1A) as reference models and all global models were resampled to reference model resolution (1m). In total, 608 million 1x1 m pixels were analyzed. To estimate the accuracy, we generated error rasters by subtracting each reference model from the corresponding global DEM and calculated descriptive statistics for this difference (e.g., median, mean, root-mean-square error (RMSE)). We also assessed the vertical accuracy as a function of the slope, slope aspect, and land cover. We found that slope had the strongest effect on DEM accuracy, with no relationship for slope aspect. The AW3D30 was the most robust and had the most stable performance in most of the tests and is therefore the best choice for an analysis of multiple geographic regions. SRTM and NASADEM also performed well where available, whereas NASADEM, as a successor of SRTM, showed only slight improvement in comparison to SRTM. MERIT and TanDEM-X also performed well despite their lower spatial resolution.
Influence of Temperature on Natural Aging Kinetics of AA6061 Modified with Sn

Al-Mg-Si alloys are widely used in cast, wrought and extruded form. A characteristic property of these alloys is the negative effect of natural pre-aging at room temperature on artificial aging. Minor additions of Sn suppress the adverse effect of room temperature aging due to controlled buffering of quenched-in excess vacancies at low temperatures. In this study we evaluate the buffering performance of Sn in the temperature range between 5 and 45 °C. This is investigated for two Sn-added AA6061 alloys with systematic variation in their Mg-, Si- and Cu-content, for comparison the natural aging kinetics of a Sn-free alloy is studied. In general a strong dependence of hardening kinetics on temperature and on chemical composition is observed. Results of aging kinetics are discussed in terms of common clustering theories and the temperature dependent trapping effect of Sn on excess vacancies.
Mesenchymal Stem Cells (MSCs) as a Potential Therapeutic Strategy in COVID-19 Patients: Literature Research

In 2019, an outbreak of an unknown coronavirus – SARS-CoV-2 – responsible for COVID-19 disease, was first reported in China, and evolved into a pandemic of huge dimensions and raised serious concerns for global health. The number of critical cases continues to increase dramatically, while vaccines and specific treatments are not yet available. There are several strategies currently being studied for the treatment of adverse symptoms of COVID-19, that encompass Acute Lung Injury (ALI)/Acute Respiratory Distress Syndrome (ARDS), extensive pulmonary inflammation, cytokine storm, and pulmonary edema, due to virus-induced pneumonia. Mesenchymal stem cells (MSCs) are at the origin of new revolutionary treatments, which may come to be applied in such as Regenerative Medicine, Immunotherapy, Tissue Engineering, and Cell and Molecular Biology due to immunomodulation and anti-inflammatory activity. MSCs have already been studied with positive outcomes for other lung pathologies, thus representing and being identified as an important opportunity for the treatment of COVID-19. It has recently been shown that these cells allow hopeful and effective therapies for serious or critical COVID-19, minimizing its adverse symptoms. In this study we will analyze the MSCs, their origin, differentiation, and therapeutic potential, making a bridge with the COVID-19 disease and its characteristics, as a potential therapeutic strategy but also reporting recent studies where these cell-based therapies were used for the treatment of COVID-19 patients.
Using Ambient Scent to Enhance Well-Being in the Multisensory Built Environment

The majority of the world’s population now lives an urban existence, spending as much as 95% of their lives indoors. The olfactory atmosphere in the built environment has been shown to exert a profound, if often unrecognized, influence over our mood and well-being. While the traditionally malodorous stench to be found indoors (i.e., prior to the invention of modern sanitation) has largely been eliminated in recent centuries, many of the outbreaks of sick-building syndrome that have been reported over the last half century have been linked to the presence of a strange smell in the environment. At the same time, however, there is also growing evidence that consumer behavior can be manipulated by the presence of pleasant ambient odors, while various aromatherapy scents are said to improve our mood and well-being. This Anglophone review focuses primarily on indoor western urban developed spaces. Importantly, the olfactory ambience constitutes but one component of the multisensory atmosphere and ambient odors interact with the visual, auditory, and haptic aspects of the built environment. Surprisingly, the majority of published studies that have deliberately chosen to combine ambient scent with other sensory interventions, such as, for example, music, have failed to increase store sales, or to enhance people’s mood and/or well-being, as might have been expected. Such negative findings therefore stress the importance of considering multisensory congruency while, at the same time, also highlighting the potential dangers that may be associated with sensory overload when thinking about the effect of ambient smell on our well-being.
Modeling Social Sensory Processing During Social Computerized Cognitive Training for Psychosis Spectrum: The Resting-State Approach

Background: Greater impairments in early sensory processing predict response to auditory computerized cognitive training (CCT) in patients with recent-onset psychosis (ROP). Little is known about neuroimaging predictors of response to social CCT, an experimental treatment that was recently shown to induce cognitive improvements in patients with psychosis. Here, we investigated whether ROP patients show interindividual differences in sensory processing change and whether different patterns of SPC are (1) related to the differential response to treatment, as indexed by gains in social cognitive neuropsychological tests and (2) associated with unique resting-state functional connectivity (rsFC). Methods: Twenty-six ROP patients completed 10 h of CCT over the period of 4–6 weeks. Subject-specific improvement in one CCT exercise targeting early sensory processing—a speeded facial Emotion Matching Task (EMT)—was studied as potential proxy for target engagement. Based on the median split of SPC from the EMT, two patient groups were created. Resting-state activity was collected at baseline, and bold time series were extracted from two major default mode network (DMN) hubs: left medial prefrontal cortex (mPFC) and left posterior cingulate cortex (PCC). Seed rsFC analysis was performed using standardized Pearson correlation matrices, generated between the average time course for each seed and each voxel in the brain. Results: Based on SPC, we distinguished improvers—i.e., participants who showed impaired performance at baseline and reached the EMT psychophysical threshold during CCT—from maintainers—i.e., those who showed intact EMT performance at baseline and sustained the EMT psychophysical threshold throughout CCT. Compared to maintainers, improvers showed an increase of rsFC at rest between PCC and left superior and medial frontal regions and the cerebellum. Compared to improvers, maintainers showed increased rsFC at baseline between PCC and superior temporal and insular regions bilaterally. Conclusions: In ROP patients with an increase of connectivity at rest in the default mode network, social CCT is still able to induce sensory processing changes that however do not translate into social cognitive gains. Future studies should investigate if impairments in short-term synaptic plasticity are responsible for this lack of response and can be remediated by pharmacological augmentation during CCT.
Psychometric Properties of the Chinese SUPPS-P Impulsive Behavior Scale: Factor Structure and Measurement Invariance Across Gender and Age

Objective: Impulsivity is widely recognized as a risk factor for a variety of mental disorders and problematic behaviors. The Short UPPS-P Impulsive Behavior Scale (SUPPS-P) is an extensively used instrument to measure impulsivity in research and clinical settings. The current study primarily aimed to evaluate the psychometric properties of the Chinese version of the SUPPS-P (C-SUPPS-P) among Chinese adolescents and emerging adults, and then to test its measurement invariance across gender and age. Methods: Data were collected from three vocational high schools and six colleges in Changsha, China. A total of 2,551 participants (20.1% male and 22.6% adolescents) completed the C-SUPPS-P and scales assessing addictive and problematic smartphone use, as well as emotional symptoms (anxiety, stress, depression). Four alternative models were examined and compared by using confirmatory factor analysis to determine the best factor structure of the C-SUPPS-P. Multigroup confirmatory factor analyses were used to test measurement invariance across gender and age. Results: A theory-driven five-factor structure consistent with the original scale was identified. All of the subscales had good internal consistency. The correlations observed with the other scales supported the construct validity of the C-SUPPS-P. Full measurement invariance was established across gender and age, and significant gender and age differences according to impulsivity facets were identified. Conclusions: The C-SUPPS-P presents a consistent factor structure, as well as reliability and validity that are equivalent to those of the original scale. The full measurement invariance shown across gender and age allows for intergroup comparisons. Overall, the C-SUPPS-P is a promising instrument to measure various impulsivity traits in Chinese adolescents and emerging adults.
PlaNet: A Neural Network for Detecting Transverse Aeolian Ridges on Mars

Transverse aeolian ridges (TARs) are unusual bedforms on the surface of Mars. TARs are common but sparse on Mars; TAR fields are small, rarely continuous, and scattered, making manual mapping impractical. There have been many efforts to automatically classify the Martian surface, but they have never explicitly located TARs successfully. Here, we present a simple adaptation of the off-the-shelf neural network RetinaNet that is designed to identify the presence of TARs at a 50-m scale. Once trained, the network was able to identify TARs with high precision (92.9%). Our model also shows promising results for applications to other surficial features like ripples and polygonal terrain. In the future, we hope to apply this model more broadly and generate a large database of TAR distributions on Mars.
Advantages of Using UAV Digital Photogrammetry in the Study of Slow-Moving Coastal Landslides

The aim of this study is to demonstrate the advantages of using micro drones in the study of large slow-moving landslides, which are widespread along the northwestern coast of Malta. In particular, attention was given to the inventory and analysis of gravity-induced joints and megaclast deposits at four study sites selected due to the presence of remarkable examples of lateral spreads evolving into block slides. The research was carried out by means of Google Earth (GE) image analysis and uncrewed aerial vehicle digital photogrammetry (UAV-DP). UAV-DP outputs enabled the identification and characterization of tens of persistent joints (locally exceeding 150 m) and permitted the size categorization of thousands of blocks. With reference to gravity-induced joints, a favorable agreement was found between existing datasets (mainly based on the integration of GE analysis and field survey) and UAV-DP outputs in terms of the identification of joints and their persistence. Conversely, the use of the UAV-DP technique showed significant advantages in terms of joint aperture determination (even exceeding 1 m) and distribution setting. Regarding the extensive megaclast deposits, UAV-DP enabled the identification of 8943 individuals which, compared with the 5059 individuals identified by GE analysis, showed an increase in the total population of 76%. This is related to the high accuracy of DP-derived orthomosaics and 3D models, which are particularly useful for identifying detached blocks. The inexpensive technique used in this research highlights its potential for being extended to other rocky coastal areas affected by slow-moving landslides.
Genome-Wide Identification and Expression Pattern Analysis of the HAK/KUP/KT Gene Family of Cotton in Fiber Development and Under Stresses

The potassium transporter family HAK/KUP/KT is a large group of proteins that are important in plant potassium transport and plays a crucial role in plant growth and development, especially in economic crops. Although HAK/KUP/KT genes have been identified in many species, research on these genes in cotton is still quite rare. In this study, in total, 21, 24, 45, and 44 HAK/KUP/KT genes were identified in Gossypium arboreum, Gossypium raimondii, Gossypium hirsutum, and Gossypium barbadense, respectively. Phylogenetic analysis showed that these genes were divided into four clusters. The G. hirsutum gene promoters contained diverse cis-regulatory elements, such as drought-responsive elements, low temperature-responsive elements, and other elements. The RNA-seq data and qRT-PCR results showed that HAK/KUP/KT genes had different expression patterns in fiber development. The qRT-PCR results of drought and NaCl treatment indicated that HAK/KUP/KT genes might play important roles in abiotic stress responses. These results will provide molecular insights into potassium transporter research in cotton.