Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Crack Extraction Performance According to Different Edge Detectors

Edges of images contain important information such as form, size, and location of objects. Thus, edge detection is an extremely important factor in image processing. In order to detect such edges, much research has been carried out, and edge detectors such as Sobel, Prewitt, Robert, Canny, and Laplacian of Gaussian (“LoG”) are universally used. This Research compares and analyzes the crack extraction function of each edge detector to automatically detect cracks occurring in concrete structures. In order to do this, simulated crack samples of various widths and contrasts were produced and attached to concrete walls, and crack images were taken from different distances. Cracks were extracted from the images taken using edge detectors like Sobel, Prewitt, Robert, Canny, and LoG, and the crack extraction performance of the edge detectors used were compared and analyzed based on the photographed distance.
Soft Decision Level Fusion Approach to a Combined Behavioral Speech-Signature Biometrics Verification

This paper describes a combined behavioral techniques based on speech and signature biometrics modalities. Fusion of multiple biometric modalities for human verification performance improvement has received considerable attention. Multi-biometric systems, which consolidate information from multiple biometric sources, are gaining popularity because they are able to overcome limitations such as non-universality, noisy sensor data, large intra-user variations and susceptibility to spoof attacks that are commonly encountered in mono modal biometric systems. Soft decision level fusion based Gaussian mixture models (GMM), in which the (EM) and (GEM) algorithms for estimating the parameters of the mixture model and the number of mixture components have been compared. The test performance of the fusion, EER=0.0 % for "EM" and EER=0.02 % for "GEM", show that the combined behavioral information scheme is more robust and have a discriminating power, which can be explored for identity authentication.
IL-10 Deficiency Protects Hamsters from Leptospira Infection

Leptospirosis is a global zoonotic disease with outcomes ranging from subclinical infection to fatal Weil’s syndrome. In addition to antibiotics, some immune activators have shown protective effects against leptospirosis. However, the unclear relationship between Leptospira and cytokines has limited the development of antileptospiral immunomodulators. In this study, the particular role of interleukin-10 (IL-10) in leptospirosis was explored by using IL-10-defective (IL-10−/−) hamsters. ABSTRACT Leptospirosis is a global zoonotic disease with outcomes ranging from subclinical infection to fatal Weil’s syndrome. In addition to antibiotics, some immune activators have shown protective effects against leptospirosis. However, the unclear relationship between Leptospira and cytokines has limited the development of antileptospiral immunomodulators. In this study, the particular role of interleukin-10 (IL-10) in leptospirosis was explored by using IL-10-defective (IL-10−/−) hamsters. After Leptospira infection, an improved survival rate, reduced leptospiral burden, and alleviation of organ lesions were found in IL-10−/− hamsters compared with wild-type (WT) hamsters. In addition, the levels of expression of the IL-1β, IL-6, and tumor necrosis factor alpha (TNF-α) genes and the level of nitric oxide (NO) were higher in IL-10−/− hamsters than in WT hamsters. Our results indicate that IL-10 deficiency protects hamsters from Leptospira infection.
Analysis of a circRNA-, miRNA-, and mRNA-associated ceRNA network reveals potential biomarkers in preeclampsia a ceRNA network in preeclampsia

Abstract Background Preeclampsia (PE), one of hypertension-related disorders of pregnancy, is a common cause of maternal death worldwide. This study aimed to identify a circRNA-miRNA-mRNA-associated ceRNA network and related pathways in PE. Material and methods We downloaded 3 microarray datasets from the Gene Expression Omnibus database, obtained 163 differentially expressed circRNAs (dif-circRNAs) (61 upregulated and 102 downregulated), 39 differentially expressed microRNAs (dif-miRNAs) (22 upregulated and 17 downregulated), and 271 differentially expressed mRNAs (dif-mRNAs) (168 upregulated and 103 downregulated) from placenta tissues of PE. Functional enrichment analysis and protein-protein interaction (PPI) network with module analysis of dif-mRNAs were performed. The regulatory relationship between dif-miRNAs and dif-mRNAs/circRNAs was predicted via related databases. A circRNA-miRNA-mRNA regulatory network was constructed. Results A total of 53 pairs were obtained, including 13 circRNAs (10 upregulated and 3 downregulated), 9 miRNAs (3 upregulated and 6 downregulated) and 31 mRNAs (22 upregulated and 9 downregulated). GNB5 and IL2RB were obtained. KEGG enrichment analysis showed that both of them were closely related with the PI3K-Akt signalling pathway. Therefore, ceRNAs might affect the PI3K-Akt signalling pathway via the upregulation of GNB5 by binding to miR-1248 in PE. Meanwhile, hsa_circ_0052661 might upregulate IL2RB by binding miR-4303 to play a role in PE in the same way. Conclusion GNB5 and IL2RB might be key genes involved in the PI3K-Akt signalling pathway in PE, and hsa_circ_0087208, hsa_circ_0035443, hsa_circ_0067557 and hsa_circ_0052661 might regulate these key genes in PE by binding miR-1248 or miR-4303. Key messages There is still a lack of predictive and diagnostic factors for preeclampsia, which is a common cause of maternal death worldwide. This study identified a novel circRNA-associated ceRNA network and related pathways in preeclampsia. GNB5 and IL2RB might be key genes in their related circRNA-associated ceRNA network, and probably take an important role in preeclampsia via PI3K-Akt signalling pathway, which made them to be potential markers of preeclampsia.
Advances in Modeling Situation Awareness, Decision Making, and Performance in Complex Operational Environments

As organizations continue to evolve and integrate even more advanced information technology capabilities, traditional cognitive models of human performance, both at the individual and team level, must similarly mature in order to flexibly adapt to the challenges faced by teams performing in today's complex operational environments. The overall goal of this panel session will be to highlight advances made in modeling situation awareness, decision making, and performance in a variety of domains and applications. The panelists draw from their varied experiences in academia and industry to offer their commentary on a diverse range of approaches to modeling these complex cognitive processes. The panel also seeks to identify critical areas warranting further investigation.
Frequency of Mismatch Repair Deficiency/High Microsatellite Instability and Its Role as a Predictive Biomarker of Response to Immune Checkpoint Inhibitors in Gynecologic Cancers

Purpose This study was to investigate the frequency of mismatch repair deficiency/high microsatellite instability (MMRd/MSI-H) in gynecologic malignancies and the efficacy of immune checkpoint inhibitors (ICIs) in patients with recurrent gynecologic cancers according to MMR/MSI status. Materials and Methods We conducted a multi-center retrospective review on the patients who were diagnosed with gynecologic cancers between 2015 and 2020. Their clinicopathologic information, results of immunohistochemistry staining for MLH1/MSH2/MSH6/PMS2 and MSI analysis, tumor response to treatment with ICIs were investigated. Results Among 1,093 patients included in the analysis, MMRd/MSI-H was most frequent in endometrial/uterine cancers (34.8%, 164/471), followed by ovarian, tubal, and peritoneal cancers (12.8%, 54/422) and cervical cancer (11.3%, 21/186). When assessed by histology without regard for cancer types, the frequency of MMRd/MSI-H was 11.0% (38/345) in high-grade serous adenocarcinoma, 38.6% (117/303) in endometrioid adenocarcinoma, and 30.2% (16/53) in carcinosarcoma. A total of 114 patients were treated with ICIs at least once. The objective response rate (ORR) was 21.6% (8/37) in cervical cancer, 4.7% (2/43) in ovarian cancer, and 25.8% (8/31) in endometrial/uterine cancers. Univariate regression analysis identified MMRd/MSI-H as the only significant factor associated with the ORR (28.9% [11/38] vs. 11.8% [9/76]; odds ratio, 3.033; 95% confidence interval, 1.129 to 8.144; p=0.028). Conclusion The frequency of MMRd/MSI-H is moderate to high in gynecologic cancers in the Korean population. MMRd/MSI-H could be effective predictive biomarkers in gynecologic cancers of any type.
Urban Air Quality Plans and Integrated Assessment Methodologies

The 2008 European Air Quality Directive (2008/50/EC) requires European Member Statesto design appropriate air quality plans (AQPs) for zones and agglomerations where the air quality does not comply with the limit values and to assess possible emission reduction measures to decreaseconcentration levels. The Portuguese agglomeration of Porto Litoral is one of the several European Union urban areas that had to develop and implement AQPs to reduce particulate matter with a 50% efficiency cut-off at 10 μm aerodynamic diameter (PM10) due to PM10 exceedances to the AQD limit values. The AQPs were initially designed based on a scenario approach and using an air quality model, which was applied over the study region for the reference situation with the current PM10 emissions, and for a reduction scenario with PM10 emissions re-estimated considering the implementation of abatement measures. The purpose was to investigate the impact on PM10 levels of the designed abatement measures. Aiming to cost-efficiently optimize Porto Litoral PM10 abatement measures the assessment procedure was repeated using an optimization approach based on the RIAT+ Integrated Assessment tool. Porto Litoral urban area’s technical and non-technical measures were characterized (including associated costs) and, through the application of the air quality model to 20 emissions abatement scenarios, Source-Receptor (S-R) relationships were created. The developed system was trained to cost-efficiently optimize abatement measures to be applied to Porto Litoral agglomeration. This paper comparatively describes the air quality plans designed to improve PM10 levels in the Porto Litoral Portuguese agglomeration based on both the scenario and the optimizationapproaches.
Developing a multicomponent implementation strategy for mental health interventions within the Nurse-Family Partnership: An application of the EPIS framework.

PURPOSE The purpose of this article is to describe the process used to create the Mental Health Innovation (MHI), a multicomponent implementation strategy that integrates evidence-based mental health interventions into the Nurse-Family Partnership (NFP), a national home visiting program delivered by nurses to low-income mothers. ORGANIZING CONSTRUCT The Exploration, Preparation, Implementation, Sustainment (EPIS) framework outlines the multistep, stakeholder-engaged process used to develop the MHI. CONCLUSION Engaging stakeholders provided an in-depth understanding of NFP infrastructure and the needs of NFP nurses and their clients. This understanding was key to designing a multicomponent implementation strategy to integrate mental health interventions within national and local NFP infrastructure and existing care processes. CLINICAL RELEVANCE Application of implementation frameworks such as EPIS provides a guide to integrating evidence-based interventions in a systematic, intentional, and rigorous manner, which in turn may promote their wide scale use and long-term sustainability.
Growth Resilience of Subarctic Rhodoliths (Lithothamnion glaciale, Rhodophyta) to Chronic Low Sea Temperature and irradiance

Rhodolith beds are pervasive marine biological systems in the subarctic North Atlantic. Limited knowledge about effects of temperature and irradiance on rhodolith growth limits the ability to anticipate the response of rhodolith beds to this ocean's chronic low, yet changing sea temperature and irradiance regimes. We carried out a 149‐d laboratory experiment with Newfoundland Lithothamnion glaciale rhodoliths to test the predictions that growth (i) is inhibited at temperatures of ~0.5°C and (ii) resumes as temperature increases above 0.5°C, albeit at a higher rate under high than low irradiances. Rhodoliths were grown in experimental tanks at near‐zero (~0.7°C) seawater temperatures during the first 85 d and at temperatures increasing naturally to ~6°C for the remaining 64 d. Rhodoliths in those tanks were exposed to either low (0.02 mol photons·m−2·d−1) or high (0.78 mol photons·m−2·d−1) irradiances during the entire experiment. Rhodoliths grew at a linear rate of ~281 μm·year−1 (0.77 μm·d−1) throughout the experiment under both irradiance treatments despite daily seawater temperature variation of up to 3°C. Near‐zero temperatures of ~0.5 to 1.0°C did not inhibit rhodolith growth. Model selection showed that PAR‐day (a cumulative irradiance index) was a better predictor of growth variation than Degree‐day (a cumulative thermal index). Our findings extend to ~0.5°C the lower limit of the known temperature range (~1 to at least 16°C) over which growth in L. glaciale rhodoliths remains unaffected, while suggesting that the growth–irradiance relationship in low‐light environments at temperatures below 6°C is less irradiance‐driven than recently proposed.
Community participation as a predictor of depressive symptoms among individuals with serious mental illnesses

Background: People with serious mental illnesses have elevated levels of depressive symptoms. Limited engagement in meaningful activities, such as work, social interactions, volunteering, and participation in faith, are one plausible explanation for this. Increased community participation over time may be associated with decreased depressive symptoms. Aim: Examine whether an increase in participation over time predicts a decrease in depression after controlling for depression at the baseline. Methods: Participants were 183 adults with schizophrenia spectrum, bipolar disorder, or major depressive disorder who completed the Hopkins Symptom Index – Depression subscale and the Temple University Community Participation Measure. Participants completed these measures at baseline and either a 12- or 24-month follow-up timepoint. Multiple regression analyses were conducted with the depression score as a dependent variable and changes in community participation as a predictor variable. Demographics, baseline depression score, and time interval between baseline and last observation were entered as control variables. Results: Endorsing more activities as important, participating in more important areas that are important, and participating ‘enough’ in more important areas over time were each significant predictors of decreases in depression. Conclusion: These findings enhance the connection between community participation and depression and suggest that a focus on participation may be important in terms of boosting both community functioning and treatment goals.
Area, isolation and climate explain the diversity of mammals on islands worldwide

Insular biodiversity is expected to be regulated differently than continental biota, but their determinants remain to be quantified at a global scale. We evaluated the importance of physical, environmental and historical factors on mammal richness and endemism across 5592 islands worldwide. We fitted generalized linear and mixed models to accommodate variation among biogeographic realms and performed analyses separately for bats and non-volants. Richness on islands ranged from one to 234 species, with up to 177 single island endemics. Diversity patterns were most consistently influenced by the islands’ physical characteristics. Area positively affected mammal diversity, in particular the number of non-volant endemics. Island isolation, both current and past, was associated with lower richness but greater endemism. Flight capacity modified the relative importance of past versus current isolation, with bats responding more strongly to current and non-volant mammals to past isolation. Biodiversity relationships with environmental factors were idiosyncratic, with a tendency for greater effects sizes with endemism than richness. The historical climatic change was positively associated with endemism. In line with theory, we found that area and isolation were among the strongest drivers of mammalian biodiversity. Our results support the importance of past conditions on current patterns, particularly of non-volant species.
Geometric frustration in the myosin superlattice of vertebrate muscle

Geometric frustration results from an incompatibility between minimum energy arrangements and the geometry of a system, and gives rise to interesting and novel phenomena. Here, we report geometric frustration in a native biological macromolecular system---vertebrate muscle. We analyse the disorder in the myosin filament rotations in the myofibrils of vertebrate striated (skeletal and cardiac) muscle, as seen in thin-section electron micrographs, and show that the distribution of rotations corresponds to an archetypical geometrically frustrated system---the triangular Ising antiferromagnet. Spatial correlations are evident out to at least six lattice spacings. The results demonstrate that geometric frustration can drive the development of structure in complex biological systems, and may have implications for the nature of the actin--myosin interactions involved in muscle contraction. Identification of the distribution of myosin filament rotations with an Ising model allows the extensive results on the latter to be applied to this system. It shows how local interactions (between adjacent myosin filaments) can determine long-range order and, conversely, how observations of long-range order (such as patterns seen in electron micrographs) can be used to estimate the energetics of these local interactions. Furthermore, since diffraction by a disordered system is a function of the second-order statistics, the derived correlations allow more accurate diffraction calculations, which can aid in interpretation of X-ray diffraction data from muscle specimens for structural analysis.
On the modelling of DC‐DC converters: An enhanced approach

DC‐DC converters are nonlinear systems that can exhibit complicated phenomena, which make difficult the system behaviour analysis and the controller design. The validity of any prediction and analysis of the converter behaviour are, mainly, related to the used modelling technique. For a rigorous description, an accurate modelling technique with minimum of simplifying assumptions is needed. In this study, a more general and simple modelling method of DC‐DC converters is proposed. It is based on introducing enhancements to the existing discrete modelling approach of DC‐DC power converters to obtain an accurate description of the system behaviour with a minimum of simplifying assumptions and validity hypothesis of the model. Copyright © 2010 John Wiley & Sons, Ltd.
Vehicle–road interaction modelling for estimation of contact forces

The main objective of this paper deals with appropriate modelling (of a vehicle and the tyre–road contact) for online estimation of contact forces. This model will be helpful for trajectory monitoring, for steering control and also for diagnosis to avoid accidents or detection of oversteering or understeering situations. A robust observer is developed for adaptive estimation of the contact forces.
Analysis of vascular dysregulation caused by infiltrating glioma cells using bold fMRI

Malignant glioma is a brain malignancy that can infiltrate into surrounding tissues causing disruption in cerebral blood flow. It is important to identify the regions of vascular dysregulation that may aid to detect the tumor spread. Also, the strength of functional connectivity within the tumor has prognostic value. The purpose of this study was to identify the vascular dysfunction caused by glioma with the help of blood oxygen level-dependent (BOLD) functional MRI (fMRI). Multiple linear regression was performed to identify the regions correlated with tumor cells. Functionally intact voxels within the tumor and the presence of Gaussian noise in BOLD fMRI images were the challenges faced to find an efficient representation for regressors. To address these challenges, we found a better representation for regressors using regional homogeneity maps derived from the tumor and control regions and was tested on images contaminated with Gaussian noise. The proposed method resulted in an improved D prime value of 2.3 which indicates the reliability of our method when compared with the state-of-the-art method.
DESIGN OF NOVEL HIGH PRESSURE- RESISTANT HYDROTHERMAL FLUID SAMPLE VALVE

Sampling study is an effective exploration method,but the most extreme environments of hydrothermal vents pose considerable engineering challenges for sampling hydrothermal fluids. Moreover,traditional sampler systems with sample valves have difficulty in maintaining samples in situ pressure. However,decompression changes have effect on microorganisms sensitive to such stresses. To address the technical difficulty of collecting samples from hydrothermal vents,a new bidirectional high pressure-resistant sample valve with balanced poppet was designed. The sample valve utilizes a soft high performance plastic "PEEK" as poppet. The poppet with inapposite dimension is prone to occur to plastic deformation or rupture for high working pressure in experiments. To address this issue,based on the finite element model,simulated results on stress distribution of the poppet with different structure parameters and preload spring force were obtained. The static axial deformations on top of the poppet were experimented. The simulated results agree with the experimental results. The new sample valve seals well and it can withstand high working pressure.
SiamRPN++D: improved SiamRPN++ using cascaded detector sensing

This paper presents a novel and robust long-term tracking algorithm to address continuous target tracking problems. The continuous target tracking demands handling of correct re-initialization of the lost target when it reappears. The main limitation of the currently popular Siamese class of deep trackers is their inability to re-initialize a target when it is lost for sufficiently long duration or when it re-appears at a location away from the lost location. Most of the Siamese class of deep trackers search for the lost targets in a limited region, close to where it disappears. Hence, they fail in automated re-initialization, tracking resumption and maintaining track after long-term occlusion or tracker-loss. This puts a serious impediment on the current state-of-the-art deep tracker frameworks for many real applications. Here, we propose integration of a lightweight and efficient Cascaded Classifier based detection mechanism with the Siamese trackers for re-initialization of the target. While the proposed approach is generic and applicable to all Siamese class of deep trackers, we have taken SiamRPN++ as a base tracker to illustrate the effectiveness of our tracking framework. The proposition enables Cascaded Classifier based detector to adaptively direct the search region for the base tracker. Extensive experimental results on the well known tracking benchmark datasets such as UAV123, VOT2019, VOT2016, VOT2018 and VOT2018-LT show that the proposed integration significantly improves the performance of the base tracker under occlusion and tracker-loss scenarios. Further, the proposed tracker improves the precision by 1.71% and the recall by 13.98% over the base tracker for the long-term tracking on the VOT2018-LT dataset.