Miracle-dz/UniFAR-FTUs huggingface dataset:
AVATAR: Adversarial self-superVised domain Adaptation network for TARget domain

This paper presents an unsupervised domain adaptation (UDA) method for predicting unlabeled target domain data, specific to complex UDA tasks where the domain gap is significant. Mainstream UDA models aim to learn from both domains and improve target discrimination by utilizing labeled source domain data. However, the performance boost may be limited when the discrepancy between the source and target domains is large or the target domain contains outliers. To explicitly address this issue, we propose the Adversarial self-superVised domain Adaptation network for the TARget domain (AVATAR) algorithm. It outperforms state-of-the-art UDA models by concurrently reducing domain discrepancy while enhancing discrimination through domain adversarial learning, self-supervised learning, and sample selection strategy for the target domain, all guided by deep clustering. Our proposed model significantly outperforms state-of-the-art methods on three UDA benchmarks, and extensive ablation studies and experiments demonstrate the effectiveness of our approach for addressing complex UDA tasks.
Cross-Shaped Windows Transformer with Self-supervised Pretraining for Clinically Significant Prostate Cancer Detection in Bi-parametric MRI

Biparametric magnetic resonance imaging (bpMRI) has demonstrated promising results in prostate cancer (PCa) detection using convolutional neural networks (CNNs). Recently, transformers have achieved competitive performance compared to CNNs in computer vision. Large scale transformers need abundant annotated data for training, which are difficult to obtain in medical imaging. Self-supervised learning (SSL) utilizes unlabeled data to generate meaningful semantic representations without the need for costly annotations, enhancing model performance on tasks with limited labeled data. We introduce a novel end-to-end Cross-Shaped windows (CSwin) transformer UNet model, CSwin UNet, to detect clinically significant prostate cancer (csPCa) in prostate bi-parametric MR imaging (bpMRI) and demonstrate the effectiveness of our proposed self-supervised pre-training framework. Using a large prostate bpMRI dataset with 1500 patients, we first pretrain CSwin transformer using multi-task self-supervised learning to improve data-efficiency and network generalizability. We then finetune using lesion annotations to perform csPCa detection. Five-fold cross validation shows that self-supervised CSwin UNet achieves 0.888 AUC and 0.545 Average Precision (AP), significantly outperforming four comparable models (Swin UNETR, DynUNet, Attention UNet, UNet). Using a separate bpMRI dataset with 158 patients, we evaluate our method robustness to external hold-out data. Self-supervised CSwin UNet achieves 0.79 AUC and 0.45 AP, still outperforming all other comparable methods and demonstrating good generalization to external data.
Application of Weighted Hausdorff Distance Algorithm in SAR/INS Scene Matching

A weighted Hausdorff distance image matching algorithm based on extracting bifurcating points on feature image is proposed.The corresponding weight formula is also put forward.A preprocessing of thinning the binary image is presented to meet the real-time need of scene matching aided navigation system.This preprocessing can reduce the redundancy of the database and speed up the global search time.Then,based on the bifurcating points extracted from thinning image,the application of the weighted Hausdorff distance algorithm to image matching can overcome the effect of speckle noise in the synthetic aperture radar(SAR) image.Simulation shows that this algorithm meet the real-time and accuracy needs of SAR/INS scene matching aided navigation system.
Automated Reasoning Support for Standpoint-OWL 2

We present a tool for modelling and reasoning with knowledge from various diverse (and possibly conflicting) viewpoints. The theoretical underpinnings are provided by enhancing base logics by standpoints according to a recently introduced formalism that we also recall. The tool works by translating the standpoint-enhanced version of the description logic SROIQ to its plain (i.e. classical) version. Existing reasoners can then be directly used to provide automated support for reasoning about diverse standpoints.
Action Recognition Based on Multi-scale Oriented Neighborhood Features

The spatio-temporal (ST) position information between local features plays an important role in action recognition task. To use the information, neighborhood-based features are built for describing local ST information around ST interest points. However, traditional methods of constructing neighborhood, such as sub-ST volumetric method and nearest-neighbor-based neighborhood method, ignore the orientation information of neighborhood. To make the neighborhood-based features more discriminative, we construct a novel, oriented neighborhood by imposing weights on the distance components. Specifically, in our scheme, firstly, local features are produced, and encoded by locality-constrained linear coding (LLC). Then, oriented neighborhoods are constructed by imposing weights on the distance components between features, and obtain single-scale oriented neighborhood features (SONFs). Next, multi-scale oriented neighborhood features (MONFs) are formed by concatenating SONFs. As a result, action video sequences are represented as a collection of MONFs. Finally, locality-constrained group sparse representation (LGSR) is used as classifier upon MONFs. Experimental results on the KTH and UCF Sports datasets show that our method achieves better performance than the competing local ST feature-based human action recognition methods.
Naringin protects against inflammation and apoptosis induced by intestinal ischemia–reperfusion injury through deactivation of cGAS‐STING signaling pathway

Effective amelioration of ischemia/reperfusion (I/R)‐induced intestinal injury and revealing its mechanisms remain the challenges in both preclinic and clinic. Potential mechanisms of naringin in ameliorating I/R‐induced intestinal injury remain unknown. Based on pre‐experiments, I/R‐injured rat intestine in vivo and hypoxia–reoxygenation (H/R)‐injured IEC‐6 cells in vitro were used to verify that naringin‐alleviated I/R‐induced intestinal injury was mediated via deactivating cGAS‐STING signaling pathway. Naringin improved intestinal damage using hematoxylin and eosin staining and decreased alanine aminotransferase and aspartate aminotransferase contents in plasma. Naringin decreased inflammation characterized by reducing IL‐6, IL‐1β, TNF‐α, and IFN‐β contents in both plasma and IEC‐6 cells. Naringin mitigated oxidative stress via recovering superoxide dismutase, glutathione, and malondialdehyde levels in the I/R‐injured intestine. Naringin reduced the expression of apoptotic proteins, including Bax, caspase‐3, and Bcl‐2, and reduced terminal deoxynucleotidyl transferase‐mediated dUTP‐biotin nick‐end labeling‐positive cells both in vivo and in vitro, and decreased Hoechst 33342 signals in vitro. cGAS, STING, p‐TBK1, p‐IRF3, and NF‐κB expressions were up‐regulated both in vivo and in vitro respectively and the up‐regulated indexes were reversed by naringin. Transfection of cGAS‐siRNA and cGAS‐cDNA significantly down‐regulated and up‐regulated cGAS‐STING signaling‐related protein expressions, respectively, and partially weakened naringin‐induced amelioration on these indexes, suggesting that deactivation of cGAS‐STING signaling is the crucial target for naringin‐induced amelioration on I/R‐injured intestine.
Blockade of Kv7 channels reverses the inhibitory effects of exchange protein directly activated by cAMP activation on purinergic contractions of the murine detrusor

Purinergic contractions of the detrusor are reduced by cAMP, but the underlying mechanisms are unclear. We examined the effects of BK and Kv7 channel modulators on purinergic contractions of the detrusor and tested if the inhibitory effects of activators of the cAMP effectors, PKA and EPAC, were reduced by blockade of BK or Kv7 channels. Purinergic contractions of the murine detrusor were induced by electric field stimulation (EFS) or application of the P2X receptor agonist α,β‐MeATP. EFS responses were inhibited by the L‐type Ca2+ channel blocker nifedipine, but not by the SERCA inhibitor CPA or the SOCE blocker GSK7975A. The Kv7 channel opener retigabine and BK channel activator compound X inhibited purinergic responses, while blockade of Kv7 or BK channels with XE991 or iberiotoxin, respectively, augmented these responses. Application of the EPAC activator 007‐AM or PKA activator 6‐MB‐cAMP inhibited EFS responses. These effects were unaffected by iberiotoxin; however, XE991 reduced the effects of 007‐AM, but not 6‐MB‐cAMP. Kv7.5 was the only Kv7 transcript detected in isolated detrusor myocytes. These data suggest that purinergic contractions of the detrusor are regulated by BK and Kv7 channels and the latter may also play a role in EPAC‐dependent inhibition of this activity.
Use of high dimensional model representation in dimensionality reduction: application to hyperspectral image classification

Recently, information extraction from hyperspectral images (HI) has become an attractive research area for many practical applications in earth observation due to the fact that HI provides valuable information with a huge number of spectral bands. In order to process such a huge amount of data in an eﬀective way, traditional methods may not fully provide a satisfactory performance because they do not mostly consider high dimensionality of the data which causes curse of dimensionality also known as Hughes phenomena. In case of supervised classiﬁcation, a poor generalization performance is achieved as a consequence resulting in availability of limited training samples. Therefore, advance methods accounting for the high dimensionality need to be developed in order to get a good generalization capability. In this work, a method of High Dimensional Model Representation (HDMR) was utilized for dimensionality reduction, and a novel feature selection method was introduced based on global sensitivity analysis. Several implementations were conducted with hyperspectral images in comparison to state-of-art feature selection algorithms in terms of classiﬁcation accuracy, and the results showed that the proposed method outperforms the other feature selection methods even with all considered classiﬁers, that are support vector machines, Bayes, and decision tree j48.
Zinc cluster transcription factors frequently activate target genes using a non-canonical half-site binding mode

Abstract Gene expression changes are orchestrated by transcription factors (TFs), which bind to DNA to regulate gene expression. It remains surprisingly difficult to predict basic features of the transcriptional process, including in vivo TF occupancy. Existing thermodynamic models of TF function are often not concordant with experimental measurements, suggesting undiscovered biology. Here, we analyzed one of the most well-studied TFs, the yeast zinc cluster Gal4, constructed a Shea–Ackers thermodynamic model to describe its binding, and compared the results of this model to experimentally measured Gal4p binding in vivo. We found that at many promoters, the model predicted no Gal4p binding, yet substantial binding was observed. These outlier promoters lacked canonical binding motifs, and subsequent investigation revealed Gal4p binds unexpectedly to DNA sequences with high densities of its half site (CGG). We confirmed this novel mode of binding through multiple experimental and computational paradigms; we also found most other zinc cluster TFs we tested frequently utilize this binding mode, at 27% of their targets on average. Together, these results demonstrate a novel mode of binding where zinc clusters, the largest class of TFs in yeast, bind DNA sequences with high densities of half sites.
Uncovering the brain‐wide pattern of synaptic input to vasopressin‐expressing neurons in the paraventricular nucleus of the hypothalamus

Arginine vasopressin (AVP) is a neuropeptide critical for the mammalian stress response and social behavior. AVP produced in the hypothalamus regulates water osmolality and vasoconstriction in the body, and in the brain, it regulates social behavior, aggression, and anxiety. However, the circuit mechanisms that link AVP to social behavior, homeostatic function, and disease are not well understood. This study investigates the circuit configurations of AVP‐expressing neurons in the rodent hypothalamus and characterizes synaptic input from the entire brain. We targeted the paraventricular nucleus (PVN) using retrograde viral tracing techniques to identify direct afferent synaptic connections made onto AVP‐expressing neurons. AVP neurons in the PVN display region‐specific anatomical configurations that reflect their unique contributions to homeostatic function, motor behaviors, feeding, and affiliative behavior. The afferent connections identified were similar in both sexes and subsequent molecular investigation of these inputs shows that those local hypothalamic inputs are overwhelmingly nonpeptidergic cells indicating a potential interneuron nexus between hormone cell activation and broader cortical connection. This proposed work reveals new insights into the organization of social behavior circuits in the brain, and how neuropeptides act centrally to modulate social behaviors.
The Brazilian version of the World Health Organization Disability Assessment Schedule (WHODAS 2.0) is reliable and valid for chronic stroke survivors

ABSTRACT Background Stroke is the leading cause of disability worldwide. Assessing stroke’s impact on patients’ daily activities and social participation can provide important complementary information to their rehabilitation process. However, no previous study had been conducted on the psychometric properties of the Brazilian version of the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) in the stroke population. Objectives This study aimed to examine the internal consistency, test-retest and inter-rater reliability, convergent validity and floor/ceiling effect of the Brazilian version of the WHODAS 2.0 in individuals after chronic stroke. Methods Two examiners interviewed 53 chronic stroke individuals who responded to the Brazilian 36-item version of the WHODAS 2.0 three times to analyze test-retest and inter-rater reliabilities. Floor/ceiling effects were calculated as relative frequencies of the lowest or the highest possible WHODAS 2.0 scores. Participants also responded to the Stroke Impact Scale 3.0 (SIS 3.0) and the Functional Independence Measure (FIM) to analyze convergent validity. Results The internal consistency analyses for domains of WHODAS showed a strong correlation among the items of each domain (0.76–0.91) except for the “getting along” domain, which presented a moderate correlation (ρ = 0,62). Total scores of WHODAS 2.0 showed satisfactory internal consistency (α = 0.93), good inter-rater reliability (ICC = 0.85), excellent test-retest reliability (ICC = 0.92) and no significant floor/ceiling effect. Convergent validity indicated moderate to strong correlations (ρ=-0.51 to ρ=-0.88; p < 0.001), with the highest values associated with the correlation with the SIS scale. Conclusions The Brazilian version of the WHODAS 2.0 instrument presented evidence of reliability and validity for chronic post-stroke individuals.
Cystic Fibrosis–Related Diabetes Workshop: Research Priorities Spanning Disease Pathophysiology, Diagnosis, and Outcomes

Cystic fibrosis (CF) is a recessive disorder arising from mutations in the gene encoding the cystic fibrosis transmembrane conductance regulator (CFTR) protein. CFTR is expressed in numerous tissues, with high expression in the airways, small and large intestine, pancreatic and hepatobiliary ducts, and male reproductive tract. CFTR loss in these tissues disrupts regulation of salt, bicarbonate, and water balance across their epithelia, resulting in a systemic disorder with progressive organ dysfunction and damage. Pancreatic exocrine damage ultimately manifests as pancreatic exocrine insufficiency that begins as early as infancy. Pancreatic remodeling accompanies this early damage, during which abnormal glucose tolerance can be observed in toddlers. With increasing age, however, insulin secretion defects progress such that CF-related diabetes (CFRD) occurs in 20% of teens and up to half of adults with CF. The relevance of CFRD is highlighted by its association with increased morbidity, mortality, and patient burden. While clinical research on CFRD has greatly assisted in the care of individuals with CFRD, key knowledge gaps on CFRD pathogenesis remain. Furthermore, the wide use of CFTR modulators to restore CFTR activity is changing the CFRD clinical landscape and the field’s understanding of CFRD pathogenesis. For these reasons, the National Institute of Diabetes and Digestive and Kidney Diseases and the Cystic Fibrosis Foundation sponsored a CFRD Scientific Workshop, 23–25 June 2021, to define knowledge gaps and needed research areas. This article describes the findings from this workshop and plots a path for CFRD research that is needed over the next decade.
Frequency affects pronoun production

Arnold, J. E. , & Griffin, Z. M. (2007). The effect of additional characters on choice of referring expression: Everyone counts. Journal of memory and language, 56(4), 521-536. Balota, D. A. , & Chumbley, J. I. (1984). Are lexical decisions a good measure of lexical access? The role of word frequency in the neglected decision stage. Journal of Experimental Psychology: Human perception and performance, 10(3), 340. Bock, J. K. , & Warren, R. K. (1985). Conceptual accessibility and syntactic structure in sentence formulation. Cognition, 21(1), 47-67. Fukumura, K. , Hyönä, J., & Scholfield, M. (2013). Gender affects semantic competition: The effect of gender in a non-gender-marking language. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(4), 1012. Hartshorne, J. K. , & Snedeker, J. (2013). Verb argument structure predicts implicit causality: The advantages of finer-grained semantics. Language and Cognitive Processes, 28(10), 1474-1508. References Referring expressions: The monk calmed the girl. [The girl (NP)/ she (pronoun)] lost her mom.
Fall Prevention Care Management

Background: Accidental falls are common among older adults and may lead to devastating consequences. One promising approach to reduce falls is to engage older adults in fall risk reduction through care management. Purpose: This article describes the implementation by undergraduate nursing students of a 6-week interdisciplinary Fall Prevention Care Management (FPCM) intervention to improve the safety of older adults living in assisted living facilities. Methods: A secondary qualitative descriptive analysis of narrative visit notes was conducted using the Meyer et al taxonomy to characterize fall prevention interventions with older adults. Results: Individualized fall prevention interventions including motivational interviewing and care management supported clients' engagement with fall prevention by facilitating behavior change related to fall prevention, helping clients identify and reflect on meaning and/or perceptions related to fall prevention. Conclusion: The FPCM project was acceptable, facilitated high fall risk older adults' engagement with fall prevention, and yielded many positive outcomes.
Effect of exercise devised to reduce arm tremor in the sighting phase of archery

Background In archery training, side bridges are performed in a posture similar to archery shooting for training the muscles around the shoulder joint and the shoulder girdle of the pusher. Aim The purpose of this study was to determine whether a low-tremor side-bridge exercise for 4 weeks improves bow tremor during archery movements. Methods Participants were 20 male college students. First, we measured the tremor during side bridges performed with trunk inclinations of 25°, 40°, 55°, and 70° using an accelerometer attached to the elbow joint and identified low-tremor side bridges. The participants were then randomly divided into intervention and non-intervention groups, and the low-tremor side bridges were performed for 4 weeks. Results The effect of the intervention was determined by measuring the total tremor value using an accelerometer attached to the bow and changes in the median power frequency (MdPF) of the middle deltoid, upper trapezius, and lower trapezius. This intervention reduced the bow tremor and the median power frequency of the middle deltoid (p < 0.05). Conclusions The findings suggested that the tremor during the archery sighting phase could be reduced by performing side bridges with a specific trunk angle for a certain period of time. This intervention was also shown to reduce the intermediate frequency of the middle deltoid. The reduced tremor can shorten the sighting phase, which can facilitate injury prevention.
Prediction of future chronic hypertension from maternal characteristics in early pregnancy

Background: Pre-eclampsia (PE) and gestational hypertension (GH) identify women at increased risk of chronic hypertension (CH) and cardiovascular disease, but as efforts to prevent PE and GH advance, fewer women at increased cardiovascular risk will be identified. Methods: Cohort of 26,511 women seen in two consecutive pregnancies. Included were women without CH, with information on maternal characteristics and blood pressure (BP) at 11-13 weeks' gestation, and development of PE or GH in the index pregnancy. Logistic regression models were fitted for prediction of development of future CH by the 20th week of the subsequent pregnancy. Performance of screening and risk calibration of the model were assessed. Results: 1560 (5.9%) women developed PE or GH (index pregnancy), and 215 (0.8%) developed future CH, a median of 3.0 years later. Predictors from the index pregnancy of development of future CH were: early pregnancy maternal age, weight and BP; Black or South Asian ethnicity; family history of PE; parity; and development of PE or GH. PE or GH accounted for 52.1% (95% confidence interval 45.2-58.9%) of future CH. At a screen-positive-rate of 10%, a model including terms for maternal characteristics and early pregnancy BP accounted for 67.9% (61.2-74.5) of future CH; addition of the development of PE or GH detected 73.5% (67.1-79.3) of future CH. Risks produced from the predictive model were well-calibrated and confirmed by five-fold cross-validation. Conclusion: Early maternal characteristics and BP are effective in predicting development of future CH. As new interventions are expected to reduce the occurrence of PE and GH, our study results offer an alternative strategy for identifying women at increased risk of future CH and are applicable worldwide.
ARF1 prevents aberrant type I IFN induction by regulating STING activation and recycling

Type I interferon (IFN) signalling is tightly controlled. Upon recognition of DNA by cyclic GMP-AMP synthase (cGAS), stimulator of interferon genes (STING) translocates along the endoplasmic reticulum (ER)-Golgi axis to induce IFN signalling. Termination is achieved through autophagic degradation or recycling of STING by retrograde Golgi-to-ER transport. Here, we identify the GTPase ARF1 as a crucial negative regulator of cGAS-STING signaling. Heterozygous ARF1 missense mutations cause a novel type I interferonopathy associated with enhanced IFN stimulated gene expression. Disease-associated, GTPase-defective, ARF1 results in increased cGAS-STING dependent type I IFN signalling in cell lines and primary patient cells. Mechanistically, mutated ARF1 perturbs mitochondrial fusion causing cGAS activation by aberrant mitochondrial DNA, and promotes accumulation of active STING at the Golgi/ERGIC due to defective retrograde transport. Our data show that ARF1 has an unexpected dual role in maintaining cGAS-STING homeostasis, through the promotion of mitochondrial fusion and STING recycling.