Miracle-dz/UniFAR-FTUs huggingface dataset:
WISE J141530.7+592234: A Very Low Mass Ratio Contact Binary with Significant Light Curve Variations

Multi-band photometric observations and period investigations of the total eclipsing binary WISE J141530.7+592234 (hereinafter J141530), whose mass ratio close to the low mass ratio limit, were carried out for the first time. The stellar atmospheric parameters of the primary component were calculated by the spectral fitting, yielding the following results: T eff = 5890 ± 22 K, [Fe/H] = 0.01 ± 0.03 dex, log g = 4.53 ± 0.04 cm s−2. Our observations show that the light curve of V-band on May 2 is about 0.1 mag brighter than that observed in February and March at phase 0.6. Comparing with the small amplitude (about 0.2 mag), the variations are remarkable. Meanwhile, obvious light curve variations and quick reversal of O’Connell effects are found in Transiting Exoplanet Survey Satellite data, which is likely caused by magnetic activity. Photometric solutions derived from multi-band light curves indicate that J141530 has a high contact degree (f ∼ 70%) and a very low mass ratio (q ∼ 0.0546). Based on the O − C diagram, a long-term period increase was found. The period increase rate is calculated to be dP/dt = 3.90 × 10−7 day yr−1, which can be explained by mass transfer from the low mass component to the large mass component. By analyzing the merging criterion, such as the ratio of spin angular momentum (J spin) to the orbital angular momentum (J orb), the instability separation and the instability mass ratio, J141530 can be regarded as a potential progenitor of luminous red novae.
Atmospheric and Fundamental Parameters of the Individual Components of Multiple Stellar Systems

We present detailed analyses of eight triple stellar systems (lying between 20 and 155 pc) and nine quadruple stellar systems (lying between 20 and 250 pc) with different configurations. Most of these systems are hierarchical. The systems are HIP 4239, HIP 5588, HIP 11072, HIP 12548, HIP 13498, HIP 17895, HIP 19915, HIP 22607, HIP 25240, HIP 28614, HIP 41171, HIP 51255, HIP 51966, HIP 54611, HIP 78977, HIP 89234, and HIP 111805. We followed a method that can be applied to all multiple stellar systems, including the main sequence and subgiant evolutionary stages, to obtain their masses, ages, and atmospheric and fundamental parameters. These parameters were assured by the combined analysis of the astrometric measurements, photometric measurements, dynamical analysis, synthetic photometry, metallicity, and positions of the components on the H-R diagram. The estimated individual masses are of higher accuracy than those given by the dynamical solutions and listed in the MSC. The results show that all components of each of these systems have precisely the same age and metallicity. This ensures that fragmentation is the most probable theory for the formation of these multiple stellar systems. A quadratic fit was calculated for the mass–luminosity relation of the main-sequence subset components. We found that the primary component in all of these systems has evolved off the main-sequence stage, and some of these stars have already entered the subgiant stage.
Distinguishing GPT-4-generated Radiology Abstracts from Original Abstracts: Performance of Blinded Human Observers and AI Content Detector

Objective: To determine GPT-4's effectiveness in writing scientific radiology article abstracts and investigate human reviewers' and AI Content detectors' success in distinguishing these abstracts. Additionally, to determine the similarity scores of abstracts generated by GPT-4 to better understand its ability to create unique text. Methods: The study collected 250 original articles published between 2021 and 2023 in five radiology journals. The articles were randomly selected, and their abstracts were generated by GPT-4 using a specific prompt. Three experienced academic radiologists independently evaluated the GPT-4 generated and original abstracts to distinguish them as original or generated by GPT-4. All abstracts were also uploaded to an AI Content Detector and plagiarism detector to calculate similarity scores. Statistical analysis was performed to determine discrimination performance and similarity scores. Results: Out of 134 GPT-4 generated abstracts, average of 75 (56%) were detected by reviewers, and average of 50 (43%) original abstracts were falsely categorized as GPT-4 generated abstracts by reviewers. The sensitivity, specificity, accuracy, PPV, and NPV of observers in distinguishing GPT-4 written abstracts ranged from 51.5% to 55.6%, 56.1% to 70%, 54.8% to 60.8%, 41.2% to 76.7%, and 47% to 62.7%, respectively. No significant difference was observed between observers in discrimination performance. Conclusion: GPT-4 can generate convincing scientific radiology article abstracts. However, human reviewers and AI Content detectors have difficulty in distinguishing GPT-4 generated abstracts from original ones.
Research on infrared image nonlinear enhancement algorithm based on wavelet analysis

Infrared image has the characteristics of low contrast and low signal noise ratio(SNR),which should be enhanced firstly in practical application.By combination of wavelet analysis and fuzzy logic,a nonlinear infrared image enhancement algorithm based on wavelet transform is proposed in this paper.First the image is decomposed by wavelet analysis and then the multi-scale feature information is extracted.Then the multi-layer band coefficients is calculated and regulated by nonlinear enhancement operator to change the intensity of target feature information.Finally the image is reconstructed by inverse wavelet transform to fulfill image contrast enhancement and background suppression.The proposed algorithm is compared with several common used image enhancement algorithms by experiment and its validity is verified.
Genomic variation associated with cardiovascular disease progression following preeclampsia: a systematic review

Background: Women with a history of preeclampsia (PE) have been shown to have up to five times the risk of developing later-life cardiovascular disease (CVD). While PE and CVD are known to share clinical and molecular characteristics, there are limited studies investigating their shared genomics (genetics, epigenetics or transcriptomics) variation over time. Therefore, we sought to systematically review the literature to identify longitudinal studies focused on the genomic progression to CVD following PE. Methods: A literature search of primary sources through PubMed, Scopus, Web of Science and Embase via OVID was performed. Studies published from January 1st, 1980, to February 02nd, 2023, that investigated genomics in PE and CVD were eligible for inclusion. Studies that did not include CVD or related risk factors as an outcome, were in non-human species or focused on pregnancy complications other than PE were excluded. Included studies were screened based on Cochrane systematic review guidelines in conjunction with the PRISMA 2020 checklist. Eligible articles were further assessed for quality using the Newcastle-Ottawa scale. Results: A total of 8929 articles were screened with 14 studies subjected to quality assessment. Following further evaluation, six studies were included for final review. All six of these studies were heterogeneous in regard to CVD/risk factors as an outcome, gene mapping approach, and in different targeted genes. The only common variable across all six studies was use of a case-control study design. Conclusions: Our results provide critical insight into the heterogeneous nature of genomic studies investigating CVD following PE and highlight the urgent need for longitudinal studies to further investigate the genetic variation underlying the progression to CVD following PE.
The influence of frailty on perioperative outcomes in patients undergoing surgical resection of liver metastases: a nationwide readmissions database study

Background Liver metastases arise frequently from primary colorectal, pancreatic, and breast cancers. Research has highlighted the patient’s frailty status as an important predictor of outcomes, but the literature evaluating the role of frailty in patients with secondary metastatic disease of the liver remains limited. Using predictive analytics, we evaluated the role of frailty in patients who underwent hepatectomy for liver metastases. Methods We used the Nationwide Readmissions Database from 2016-2017 to identify patients who underwent resection of a secondary malignant neoplasm of the liver. Patient frailty was evaluated using the Johns Hopkins Adjusted Clinical Groups (JHACG) frailty-defining diagnosis indicator. Propensity score matching was performed and Mann-Whitney U testing was used to analyze complication rates. Receiver operating characteristic (ROC) curves were created following creation of logistic regression models for predicting discharge disposition. Results Frail patients reported significantly higher rates of nonroutine discharges, longer inpatient stays, greater costs, higher rates of acute infection, posthemorrhagic anemia, urinary tract infection (UTI), deep vein thrombosis (DVT), wound dehiscence and readmission, and greater mortality (P<0.05). Predictive models for patient discharge disposition, DVT and UTI demonstrated that the use of frailty status and age improved the area under the ROC curves significantly compared to models using age alone. Conclusions Frailty was found to be significantly correlated with higher rates of medical complications during inpatient stay following hepatectomy in patients with liver metastasis. The inclusion of patient frailty status in predictive models improved their predictive capacity compared to those using age alone.
Cirrhotic patients on proton pump inhibitors are at a twofold risk of spontaneous bacterial peritonitis independently of gastrointestinal bleeding: a population-based retrospective study

Background Recent findings suggest that cirrhotic patients on proton pump inhibitors (PPIs) are at a higher risk for developing spontaneous bacterial peritonitis (SBP) than non-PPI users. We aimed to identify whether PPI use is an independent risk factor for the development of SBP among cirrhotic patients in the United States (US). Methods We enrolled a retrospective cohort using a validated multicenter database. Patients with a SNOMED-CT diagnosis of “cirrhosis” between 1999 and 2022 were identified. All patients below 18 years of age were excluded. We calculated the prevalence of individuals using PPIs in the total US population and in cirrhotic patients from 1999 to date, and the incidence of SBP in the past year. Finally, we constructed a multivariate regression model, controlling for multiple covariates. Results The final analysis included 377,420 patients. The 20-year-period prevalence of SBP in patients with cirrhosis was 3.54% and the prevalence of patients using PPIs in the US population was 12,000 per 100,000 people (12.00%). The 1-year incidence of SBP in cirrhotic patients using PPIs was 2500 per 100,000 people. After accounting for confounders, the risk of SBP was higher among males, patients with a diagnosis of gastrointestinal bleeding, and those using β-blockers and PPIs. Conclusions To date, this is the largest cohort used to examine the prevalence of SBP among cirrhotic patients in the US. PPI use and hepatic encephalopathy offered the highest risk for the development of SBP, independently of gastrointestinal bleeding. Focusing on judicious PPI use should be encouraged among cirrhotic patients.
Evaluation of oral and topical bovine colostrum compared to mesalamine in the treatment of animal model of acetic acid-induced ulcerative colitis

Background Oxidative activity and inflammatory responses have been shown to play a pivotal role in the pathogenesis of ulcerative colitis (UC). Colostrum is a natural product with anti-inflammatory and antioxidative properties. Methods UC was induced in 37 Sprague Dawley rats by administration of a 2 mL enema of 3% acetic acid (AA). The control groups received no treatment during the study, while the experimental groups received either oral or rectal administration of 100 mg/kg 5-aminosalicylic acid, or oral or rectal administration of 300 mg/kg of colostrum. Histopathological and serological analyses were performed 7 days following treatment. Results A significant decrease in weight was seen in all rats except for the test groups receiving colostrum (P<0.001). After treatment, the level of superoxide dismutase increased more significantly in the test groups that received colostrum (P<0.05). All test groups had a reduction in C-reactive protein and white blood cell levels. The colostrum test groups also showed a decrease in inflammation rate, ulceration, destruction, disorganization, and crypt abscess of the colonic mucosa. Conclusions The findings of this study show that the administration of colostrum can improve the pathological changes of the intestinal mucosa, as well as inflammatory responses, in animal models of UC. Further studies at both preclinical and clinical levels are suggested to confirm these findings.
Intrinsic, widefield optical imaging of hemodynamics in rodent models of Alzheimer’s disease and neurological injury

Abstract. The complex cerebrovascular network is critical to controlling local cerebral blood flow (CBF) and maintaining brain homeostasis. Alzheimer’s disease (AD) and neurological injury can result in impaired CBF regulation, blood–brain barrier breakdown, neurovascular dysregulation, and ultimately impaired brain homeostasis. Measuring cortical hemodynamic changes in rodents can help elucidate the complex physiological dynamics that occur in AD and neurological injury. Widefield optical imaging approaches can measure hemodynamic information, such as CBF and oxygenation. These measurements can be performed over fields of view that range from millimeters to centimeters and probe up to the first few millimeters of rodent brain tissue. We discuss the principles and applications of three widefield optical imaging approaches that can measure cerebral hemodynamics: (1) optical intrinsic signal imaging, (2) laser speckle imaging, and (3) spatial frequency domain imaging. Future work in advancing widefield optical imaging approaches and employing multimodal instrumentation can enrich hemodynamic information content and help elucidate cerebrovascular mechanisms that lead to the development of therapeutic agents for AD and neurological injury.
Sociobiome - Individual and neighborhood socioeconomic status influence the gut microbiome in a multi-ethnic population in the US

Lower socioeconomic status (SES) is related to increased incidence and mortality due to chronic diseases in adults. Association between SES variables and gut microbiome variation has been observed in adults at the population level, suggesting that biological mechanisms may underlie the SES associations; however, there is a need for larger U.S. studies that consider individual- and neighborhood-level measures of SES in racially diverse populations. In 825 participants from a multi-ethnic cohort, we investigated how SES shapes the gut microbiome. We determined the relationship of a range of several individual- and neighborhood-level SES indicators with the gut microbiome. Individual education level and occupation were self-reported by questionnaire. Geocoding was applied to link participants’ addresses with neighborhood census tract socioeconomic indicators, including average income and social deprivation in the census tract. Gut microbiome was measured using 16SV4 region rRNA gene sequencing of stool samples. We compared α-diversity, β-diversity, and taxonomic and functional pathway abundance by socioeconomic status. Lower SES was significantly associated with greater α-diversity and compositional differences among groups, as measured by β-diversity. Several taxa related to low SES were identified, especially an increasing abundance of Genus Catenibacterium and Prevotella copri. The significant association between SES and gut microbiota remained even after considering the race/ethnicity in this racially diverse cohort. Together, these results showed that lower socioeconomic status was strongly associated with compositional and taxonomic measures of the gut microbiome, suggesting that SES may shape the gut microbiota.
Infectious proctitis: what every gastroenterologist needs to know

The incidence of sexually transmitted infections (STI) is rising, especially in high-risk groups, namely people living with human immunodeficiency virus (HIV), men who have sex with men, and people with multiple sexual partners. Additionally, the growing availability and use of pre-exposure prophylaxis to prevent HIV infection appears to be associated with an increased risk of infection by venereal agents. The correct recognition of these infections is crucial, not only for individual patients, but also in terms of public health. Furthermore, a diligent diagnostic assessment is key for an efficient therapeutic approach. Infectious proctitis (IP) predominantly occurs in individuals with a history of receptive anal exposure, being a frequent cause for referral to a gastroenterology specialist. The most frequently identified agents are Neisseria gonorrhoeae, Chlamydia trachomatis, Herpes simplex virus, and Treponema pallidum. This paper aims to provide a practice-oriented and up-to-date review regarding the diagnostic and therapeutic approaches to patients with suspected IP. The authors reviewed the most important issues in terms of clinical history, physical examination, and specific diagnostic and therapeutic methods. It is also highlighted the most important topics regarding vaccination, screening for other STIs and differential diagnosis with inflammatory bowel disease. Identification of high-risk groups, screening of potential STIs, and notification of diagnosed anorectal diseases are extremely important and essential to prevent transmission and other complications.
Simulation of climate change over europe using a nested regional‐climate model. II: Comparison of driving and regional model responses to a doubling of carbon dioxide

Results are assessed from a 10‐year simulation of the equilibrium response to doubled carbon dioxide (CO2) over Europe made with a nested high‐resolution regional‐climate model (RCM). the simulated changes are compared against those produced by the driving global general‐circulation model (GCM). the domain‐averaged increases in temperature and moisture content are similar in both models. Because of a stronger hydrological cycle the increases in precipitation and evaporation are larger in the RCM than in the GCM, whereas the reductions in lower and middle tropospheric relative humidity and cloud cover are smaller.
Dynamic Aether as a Trigger for Spontaneous Spinorization in Early Universe

In the framework of the Einstein–Dirac-aether theory we consider a phenomenological model of the spontaneous growth of the fermion number, which is triggered by the dynamic aether. The trigger version of spinorization of the early Universe is associated with two mechanisms: the first one is the aetheric regulation of behavior of the spinor field; the second mechanism can be related to a self-similarity of internal interactions in the spinor field. The dynamic aether is designed to switch on and switch off the self-similar mechanism of the spinor field evolution; from the mathematical point of view, the key of such a guidance is made of the scalar of expansion of the aether flow, proportional to the Hubble function in the isotropic cosmological model. Two phenomenological parameters of the presented model are shown to be considered as factors predetermining the total number of fermions born in the early Universe.
Spatial-Temporal Networks for Antibiogram Pattern Prediction

An antibiogram is a periodic summary of antibiotic resistance results of organisms from infected patients to selected antimicrobial drugs. Antibiograms help clinicians to understand regional resistance rates and select appropriate antibiotics in prescriptions. In practice, significant combinations of antibiotic resistance may appear in different antibiograms, forming antibiogram patterns. Such patterns may imply the prevalence of some infectious diseases in certain regions. Thus it is of crucial importance to monitor antibiotic resistance trends and track the spread of multi-drug resistant organisms. In this paper, we propose a novel problem of antibiogram pattern prediction that aims to predict which patterns will appear in the future. Despite its importance, tackling this problem encounters a series of challenges and has not yet been explored in the literature. First of all, antibiogram patterns are not i.i. d as they may have strong relations with each other due to genomic similarities of the underlying organisms. Second, antibiogram patterns are often temporally dependent on the ones that are previously detected. Furthermore, the spread of antibiotic resistance can be significantly influenced by nearby or similar regions. To address the above challenges, we propose a novel Spatial-Temporal Antibiogram Pattern Prediction framework, STAPP, that can effectively leverage the pattern correlations and exploit the temporal and spatial information. We conduct extensive experiments on a real-world dataset with antibiogram reports of patients from 1999 to 2012 for 203 cities in the United States. The experimental results show the superiority of STAPP against several competitive baselines.
Multivariate Clustering Procedures with Variable Metrics

In this work we discuss several methods used in the clustering of obj ects which can be represented as points in Euclidean space. Moreover, only those procedures are considered that lead to partition of a sample into a preestablished number of groups, although some ideas are also valid for hierarchical schemes (Lance and Williams [1966]). There are two major approaches to this problem. In the first one (which could be called "metric") a measure of distance is defined between each point x of the sample and each subset G thereof (an (i, k)-measure in the terminology of Lance and Williams [1968]). An initial partition is generated (for instance at random, or based on some external considerations) and then the points are successively reassigned to the "nearest" group, until no more reallocations are possible (or desired). In the second approach, each partition is assigned a numerical value, usually measuring the reduction of uncertainty due to grouping, and a search is made for partitions that optimize this functional (Friedman and Rubin [1967], Rubin [1967]). The simplest and most commonly used metric is the Euclidean distance between x and the mean of G (Ball and Hall [1967], Forgy [1965], MacQueen [1967]). In spite of its practical advantages, it has the drawback that the results it produces are not invariant under nonsingular linear transformations of the data (e.g., changes in the measurement units). One could avoid this drawback if he knew the within groups covariance matrix W corresponding to the "correct" partition he was looking for. Then the most natural metric would be Mahalanobis distance based on W. A possible solution to this dilemma is at each step to use the Mahalanobis metric induced by the matrix W corresponding to the current partition. A second conceivable improvement is obtained when one tries to overcome the fact that in the two former cases the metric is the same for all groups. If he suspects that the "true" clusters may have very different covariance structures, it would be reasonable to let each cluster have its own metric, based on its current covariance matrix. This was advocated by Chernoff [1970] and Rohlf [1970].