Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain morphology changes after spinal cord injury: A voxel-based meta-analysis

Objectives Spinal cord injury (SCI) remodels the brain structure and alters brain function. To identify specific changes in brain gray matter volume (GMV) and white matter volume (WMV) following SCI, we conducted a voxel-based meta-analysis of whole-brain voxel-based morphometry (VBM) studies. Methods We performed a comprehensive literature search on VBM studies that compared SCI patients and healthy controls in PubMed, Web of Science and the China National Knowledge Infrastructure from 1980 to April 2022. Then, we conducted a voxel-based meta-analysis using seed-based d mapping with permutation of subject images (SDM-PSI). Meta-regression analysis was performed to identify the effects of clinical characteristics. Results Our study collected 20 studies with 22 GMV datasets and 15 WMV datasets, including 410 patients and 406 healthy controls. Compared with healthy controls, SCI patients showed significant GMV loss in the left insula and bilateral thalamus and significant WMV loss in the bilateral corticospinal tract (CST). Additionally, a higher motor score and pinprick score were positively related to greater GMV in the right postcentral gyrus, whereas a positive relationship was observed between the light touch score and the bilateral postcentral gyrus. Conclusion Atrophy in the thalamus and bilateral CST suggest that SCI may trigger neurodegeneration changes in the sensory and motor pathways. Furthermore, atrophy of the left insula may indicate depression and neuropathic pain in SCI patients. These indicators of structural abnormalities could serve as neuroimaging biomarkers for evaluating the prognosis and treatment effect, as well as for monitoring disease progression. The application of neuroimaging biomarkers in the brain for SCI may also lead to personalized treatment strategies. Systematic review registration https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42021279716, identifier: CRD42021279716.
Process-based modeling of soil nitrous oxide emissions from United States corn fields under different management and climate scenarios coupled with evaluation using regional estimates

Direct emissions of soil nitrous oxide during a growing season (N2Ogs) can be quantified with process-based models considering interactions between management, climate, and soil moisture when key data are available. We used an adapted “parameterized CENTURY/DAYCENT-model” (pCENTURY) calibrated with crop growth and soil organic matter decay coefficients at the county-level for the estimation of N2Ogs in the United States Corn Belt. Model estimated N2O-emissions from corn-based biofuels scenarios considering crop rotation, fertilizer inputs, tillage, and weather were compared against meta-summary of field observations from 55 studies. Both model and meta-summary ranked N2Ogs-emissions to be corn > wheat > soybean phase while model likely underestimated cover crop N2Ogs-emissions. The N2Ogs-emissions and the associated emission factors (EFs) were modeled and summarized to be greater after anhydrous ammonia than urea application and from conventional tilled than non-tilled fields. Modeled and observed N2Ogs-emissions after organic and inorganic fertilizer amendment did not differ due to high variability associated with the treatments. However, the organic fertilizer associated EFs were greater according to meta-summary data because of N input rates. Regionalized weather scenarios indicate hotspots for N2Ogs-emissions can occur where crop N uptake is limited during dry years and in eastern states also during normal or wet seasons. The pCENTURY-derived N2Ogs EFs (0.91 ± 0.19%) for counties investigated were only slightly lower than literature (1.07 ± 0.57%) or Tier-1 (1%) values. Our preliminary evaluation of regional soil moisture estimates showed reasonable agreement between monthly soil moisture estimates and the North American Soil Moisture Dataset during the growing season, but overestimation of soil moisture in winter-spring can influence the estimates of annual N2O emissions so future work is needed to calibrate soil moisture-associated model parameters. Our work provided scenario-based estimates of climate and management impacts on soil N2Ogs-emissions together with valuable spatial insights into EFs that will be improved by more accurate information of fertilizer inputs and more temporally refined model evaluation.
No evidence for association between late pregnancy maternal cortisol and gray matter volume in a healthy community sample of young adolescents

A compelling amount of animal and human research has shown that perceived maternal stress during pregnancy can affect the neurodevelopment of the offspring. Prenatal maternal cortisol is frequently proposed as the biological key mechanism underlying this link; however, literature that investigates the effects of prenatal cortisol on subsequent neurodevelopment in humans is scarce. By using longitudinal data from a relatively large community sample of mother–child dyads (N = 73), this pre-registered study prospectively examined the role of maternal prenatal cortisol concentrations on subsequent individual differences in gray matter volume (GMV) and hippocampal subfield volumes at the onset of puberty of the offspring (12 years of age). Two markers of cortisol, that is, evening cortisol and circadian decline over the day, were used as indicators of maternal physiological stress during the last trimester of pregnancy. The results indicate that prenatal maternal cortisol levels were not associated with GMV or hippocampal subfield volumes of the children. These findings suggest that late pregnancy maternal cortisol may not be related to the structural development of the offspring’s brain, at least not in healthy community samples and at the onset of puberty. When examining the influence of prenatal stress on offspring neurodevelopment, future investigations should delineate gestational timing effects of the cortisol exposure, cortisol assessment method, and impact of additional biomarkers, as these were not investigated in this study.
Stress‐dependent hardening and failure surfaces of dry sand

During several triaxial compression experiments on plastic hardening, softening, and failure properties of dense sand specimens, it was found on various stress paths that the size of the failure surface was not constant. Instead, it changed depending on the current state of hydrostatic pressure. This finding is in contrast to the standard opinion consisting of the fact that the failure surface remains constant, once it has been reached during an experiment or in situ.
Vibro-Tactile Stimulation for Finger Discrimination in P300 BCI for Post-Stroke Rehabilitation: Study on Healthy Subjects

Currently, rehabilitation of post-stroke patients is an actual medical task. Actively developing technologies of brain-computer interfaces, based on the process of motor imagery, are already used in clinical practice for rehabilitation tasks. However, they have a small number of commands while provided control is anthropomorphic. One of the alternatives is the use of BCI based on vibro-tactile P300. Nevertheless, the selection of stimulation parameters for stable registration of the P300 is still an actual task. Moreover, application of vibro-tactile stimulation affecting the individual fingers of the hand makes it possible to restore fine motor skills. For this purpose, two different versions of the of vibro-tactile stimulator layouts were developed. In this study such exposure parameters as the duration of stimuli in the range from 40 to 600 ms and the frequency of stimulation from 1 to 2 Hz were considered. Different types of vibration motors also varied. The values of amplitudes and latencies of the evoked potentials P300 in the leads Cz and Pz were obtained. The difference between typical and registered latency values can be associated with a long transient process of vibration motors, which was confirmed by the quantitative assessment. Conclusions about the recommended stimulation mode are made and further plans for the modification of the stand are indicated.
Analysis and simulations of a Viscoelastic Model of Angiogenesis

The work analyzes a one-dimensional viscoelastic model of blood vessel growth under nonlinear friction with surroundings, and provides numerical simulations for various growing cases. For the nonlinear differential equations, two sufficient conditions are proven to guarantee the global existence of biologically meaningful solutions. Examples with breakdown solutions are captured by numerical approximations. Numerical simulations demonstrate this model can reproduce angiogenesis experiments under various biological conditions including blood vessel extension without proliferation and blood vessel regression.
Improved Transformer With Multi-Head Dense Collaboration

Recently, the attention mechanism boosts the performance of many neural network models in Natural Language Processing (NLP). Among the various attention mechanisms, Multi-Head Attention (MHA) is a powerful and popular variant. MHA helps the model to attend to different feature subspaces independently which is an essential component of Transformer. Despite its success, we conjecture that the different heads of the existing MHA may not collaborate properly. To validate this assumption and further improve the performance of Transformer, we study the collaboration problem for MHA in this paper. First, we propose the Single-Layer Collaboration (SLC) mechanism to help each attention head improve its attention distribution based on the feedback of other heads. Furthermore, we extend SLC to the cross-layer Multi-Head Dense Collaboration (MHDC) mechanism. MHDC helps each MHA layer learn the attention distributions considering the knowledge from the other MHA layers. Both SLC and MHDC are implemented as lightweight modules with very few additional parameters. When equipped with these modules, our new framework, i.e., Collaborative TransFormer (CollFormer), significantly outperforms the vanilla Transformer on a range of NLP tasks, including machine translation, sentence semantic relatedness, natural language inference, sentence classification, and reading comprehension. Besides, we also carry out extensive quantitative experiments to analyze the properties of the MHDC in different settings. The experimental results validate the effectiveness and universality of MHDC as well as CollFormer.
Local Detail Enhancement Network for CNV Typing in OCT Images

Choroidal neovascularization (CNV) is one of the severe eye disease. The severe results will cause of loss of acuity, scotomata, and distortion of vision. Automatic and accurate classification of CNV with optical coherence tomography (OCT) images can assist doctors in treatment. However, the existing methods ignore the fact that semantic feature maps, used for classification, lose much feature detail information. Therefore, we proposed a local detail enhancement network for CNV classification, which includes both progressive training mode and local detail enhancement (LDE) module. With the progressive training mode, the learned features fuse shallow and stable fine-grained information with high-level semantic information, which promote the diversity of the learned features. In LDE module, the detail feature learn (DFL) module is introduced to learn the underlying detail information and embed it into the semantic feature map. The semantic feature map with detail information is propitious to capture the subtle discrepancy between different CNV types and promote the classification performance. Sufficient experiments are performed on our self-build CNV dataset. Our method excelled existing methods and in evaluation indicators ACC, AUC, SEN, and SPE are 92.3%, 87.1%, 91.5%, and 90.9%.
Accurate 3D viscous incompressible flow calculations with the FEM

A second-order-accurate (in both time and space) formulation is developed and implemented for solution of the three-dimensional incompressible Navier-Stokes equations involving high-Reynolds-number flows past complex configurations. For stabilization, only a fourth-order-accurate artificial dissipation term in the momentum equations is used. The finite element method (FEM) with an explicit time-marching scheme based on two-fractional-step integration is used for solution of the momentum equations. The element-by-element (EBE) technique is employed for solution of the auxiliary potential function equation in order to ease the memory requirements for matrix. The cubic cavity problem, the laminar flow past a sphere at various Reynolds numbers and the flow around the fuselage of a helicopter are successfully solved.
Aerobic Exercise System for Home Telerehabilitation

The COVID-19 pandemic has impacted every aspect of health delivery and encouraged to replace in-person clinical visits with telecommunications. By providing wireless communication between embedded electronic devices and sensors, telerehabilitation enables constant monitoring of vital body functions, and tracking of physical activities of a person and aids physical therapy. In this paper, we designed and tested two remotely controlled versions of interactive bike (iBikE) systems which communicate through either Wi-Fi or BLE and give the clinical team the capability to monitor exercise progress in real time using simple graphical representation. We used the same hardware and user interface for both designs. The software uses either Wi-Fi or BLE protocol to connect the iBikE equipment and PC tablet. The bike can be used for upper or lower limb rehabilitation. A customized tablet app was developed to provide user interface between the app and the bike sensors. Both bikes were tested with a single group of nine individuals in two separate sessions. Each individual was asked to hand-cycle for three separate sub-sessions (1 minute each for slow, medium, and fast pace) with one-minute rest. During each sub-session, speed of the bikes was measured continuously using a tachometer, in addition to reading speed values from the iBikE app, to compare the functionality and accuracy of the measured data. Measured RPMs in each sub-session from iBikE and tachometer were further divided into 4 categories: 10-second bins (6 bins), 20-second bins (3 bins), 30-second bins (2 bins), and RPMs in each sub-session (1 minute, 1 bin). Then, the mean difference of each category (iBikE, tachometer) was calculated for each sub-session. Finally, mean and standard deviation (SD) of the calculated mean differences were reported for all individuals. We saw decreasing trend in both mean and SD from 10 second to 1 minute measurement. For BLE iBikE system, minimum mean RPM difference was $0.2 \pm 0.3$ in one-minute sub-session with medium speed. This number was $0.21 \pm 0.21$ in one-minute sub-session with slow speed for Wi-Fi iBikE system. Thus, testing confirmed high accuracy of our interfaces.
Generic Concept for Integrating Voice Assistance Into Smart Therapeutic Interventions

Therapeutic Interventions (TIs) play an important role in modern medical and psychological treatments, but their integration into the digital world still shows deficits, e.g., in the integration of the auditory interface. Initiatives to integrate this interface into existing Internet- and Mobile-Based Interventions (IMIs) are largely focused on a small group of Voice Assistants (VAs) and their specific capabilities. To mitigate these drawbacks, the presented concept seamlessly integrates arbitrary VAs into the treatment process of TIs. To this end, an architecture - including a discussion of relevant requirements - is presented that, on the one hand, uses VAs as the only point of contact with patients and, on the other hand, provides a comprehensive web-based backend for Healthcare Providers (HCPs). Based on the architecture, a proof-of-concept implementation using Amazon Alexa is presented. Finally, it is discussed that the scenario addressed and the solution presented have great potential, but still need a lot of work and technical considerations.
The Bantu-Romance connection: a comparative investigation of verbal agreement, DPs, and information structure

1. Acknowledgments 2. List of contributors 3. Introduction 4. Part 1. Clitics and agreement 5. Concepts of structural underspecification in Bantu and Romance (by Marten, Lutz) 6. On different types of clitic clusters (by Cardinaletti, Anna) 7. Pronominal object markers in Romance and Bantu (by Labelle, Marie) 8. The Bantu-Romance connection in verb movement and verbal inflectional morphology (by Harford, Carolyn) 9. Part 2. The structure of DPs 10. DP in Bantu and Romance (by Carstens, Vicki) 11. On the interpretability of phi-features (by Zamparelli, Roberto) 12. Agreement and concord in nominal expressions (by Giusti, Giuliana) 13. A unified syntactic analysis of Italian and Luganda nouns (by Ferrari-Bridgers, Franca) 14. Part 3. Information structure 15. The fine structure of the Topic field (by Frascarelli, Mara) 16. Focus at the interface: Evidence from Romance and Bantu (by Costa, Joao) 17. Agreement in thetic VS sentences in Bantu and Romance (by Wal, Jenneke van der) 18. Index of languages 19. General index
HANDS: enHancing Academic performaNce via Deep foreSt

Student performance prediction plays a critical role in numerous educational scenarios, e.g., academic early warning and personalized teaching. A large body of researches have been developed for better learning gains through leveraging plentiful student-related information, such as students' historical course grades and demographical data. Recent years, campus smartcards have been widely used in most of Chinese universities, and a large amount of students' behavioral data can be recorded in an unobtrusive style, which provides a new perspective for us to predict students' academic performance. Different from most of traditional approaches, in this study, we try to exploit students' campus behavioral data, and present a novel approach for student performance prediction, namely as HANDS (enHancing Academic performaNce via Deep foreSt), which introduces decision tree-based deep learning method into establishing the predictive models. Particularly, benefiting from end-to-end learning style of deep learning, the proposed HANDS method can automatically extract students' behavioral characteristics and predict their academic performance. And thus it can save expensive human labor cost, compared with handcrafted feature-based approaches. Experimental results on a real-world data set demonstrate the superiority of our approach over the state-of-the-art methods.
Knockout and Double Knockout of Cathepsin K and Mmp9 reveals a novel function of Cathepsin K as a regulator of osteoclast gene expression and bone homeostasis

Cathepsins play a role in regulation of cell function through their presence in the cell nucleus. However, the role of Cathepsin K (Ctsk) as an epigenetic regulator in osteoclasts remains unknown. Our data demonstrated that Ctsk-/-Mmp9-/- mice have a striking phenotype with a 5-fold increase in bone volume compared with WT. RNA-seq analysis of Ctsk-/-, Mmp9-/- and Ctsk-/-/Mmp9-/- osteoclasts revealed their distinct functions in gene expression regulation, including reduced Cebpa expression, increased Nfatc1 expression, and in signaling pathways activity regulation. Western blots and qPCR data validated these changes. ATAC-seq profiling of Ctsk-/-, Mmp9-/-, and Ctsk-/-/Mmp9-/- osteoclasts indicated the changes resulted from reduced chromatin openness in the promoter region of Cebpa and increased chromatin openness in Nfatc1 promoter in Ctsk-/-/Mmp9-/- osteoclasts compared to that in osteoclasts of WT, Ctsk/- and Mmp9-/-. We found co-localization of Ctsk with c-Fos and cleavage of H3K27me3 in wild-type osteoclasts. Remarkably, cleavage of H3K27me3 was blocked in osteoclasts of Ctsk-/- and Ctsk-/-/Mmp9-/- mice, suggesting that Ctsk may epigenetically regulate distinctive groups of genes' expression by regulating proteolysis of H3K27me3. Ctsk-/-/Mmp9-/- double knockout dramatically protects against ovariectomy induced bone loss. We found that Ctsk may function as an essential epigenetic regulator in modulating levels of H3K27me3 in osteoclast activation and maintaining bone homeostasis. Our study revealed complementary and unique functions of Ctsk as epigenetic regulators for maintaining osteoclast activation and bone homeostasis by orchestrating multiple signaling pathways and targeting both Ctsk and Mmp9 is a novel therapeutic approach for osteolytic diseases such as osteoporosis.
The Criterion-Oriented Three-Way Ranking and Clustering Strategies in Fuzzy Decision Environments

Faced with any decision-making problems with fuzzy multicriteria information, decision-makers generally set a minimum requirement on each criterion for satisfying their own preferences, thereby forming a fuzzy set on the criterion universe, which is called the criterion fuzzy set. From the perspective of realistic decision, the final decision of all alternatives should be determined according to this criterion fuzzy set. In view of this, this article proposes the criterion-oriented three-way ranking and clustering strategies, which can solve the qualitative clustering and ranking problems of all alternatives from the perspective of criterion fuzzy sets. First, we define a criterion fuzzy set as a criterion-oriented fuzzy concept and propose a criterion-oriented relative risk loss model and discuss related properties accordingly. Meanwhile, we use the generalized fuzzy rough lower (upper) approximation to estimate the absolute (relative) conditional probability between the binary fuzzy class of the alternative and the criterion-oriented fuzzy concept. Then, a criterion-oriented absolute (relative) three-way clustering strategy is proposed, which can perform qualitative analysis on all alternatives. Furthermore, based on the three-way semantics and global cost function, we recommend a criterion-oriented absolute (relative) three-way ranking strategy, which can rank all alternatives. Finally, through numerical example, comparative analysis and sensitivity analysis, we test the feasibility and effectiveness of the proposed criterion-oriented three-way ranking and clustering strategies.
Mirrored strain-balanced quantum well concentrator cells in the radiative limit

Strain-balanced Quantum Well Solar Cells (SB- QWSCs) are radiatively dominated at concentrator current levels. Incorporating back surface mirrors on the back of the doped substrate leads to a reduction in this radiative recombination current while the non-radiative dark current at lower bias remains unchanged. This work extends a previous model of radiative dark currents to cells where the substrate is not a perfectly absorbing sink for emitted luminescence by including multiple passes of photons emitted by radiative recombination. The luminescence in such mirrored structures is reduced and the radiative dark current lower. The structure is suited to concentrator applications because it corresponds to the high efficiency limit where losses due to light re-emission are limited to the solid angle for absorption of solar radiation.