Miracle-dz/UniFAR-FTUs huggingface dataset:
Return to Baseline Physical Activity After Bone–Patellar Tendon–Bone Versus Hamstring Tendon Autografts for Anterior Cruciate Ligament Reconstruction: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Background: Bone–patellar tendon–bone (BPTB) and hamstring tendon (HT) autografts are the most utilized grafts for primary anterior cruciate ligament (ACL) reconstruction. The ability of a patient to return to a preinjury level of physical activity is a key consideration in choice of graft; the influence of graft choice on this metric lacks consensus in the literature. Purpose: To assess the effects of autograft choice (BPTB vs HT) for primary ACL reconstruction on return to baseline level of physical activity and/or sports participation. Study Design: Meta-analysis; Level of evidence, 1. Methods: A systematic review of randomized controlled trials comparing the use of BPTB and HT autografts for primary ACL reconstruction was conducted. The electronic databases EMBASE, MEDLINE, Cochrane CENTRAL, and Web of Science were comprehensively queried through September 23, 2019. The primary outcome was return to preinjury level of activity/sports. Secondary outcomes included knee stability testing (Lachman, KT-1000 arthrometer, and pivot-shift tests) and clinical subjective knee scores (Tegner, Cincinnati, International Knee Documentation Committee, and Lysholm). Two independent reviewers were involved in the screening of titles and abstracts, data extraction, and the assessment of risk of bias. Meta-analyses were performed respecting the Cochrane Handbook for Systematic Reviews of Intervention. Results: A total of 29 studies (N = 3099 patients) were eligible for this review, of which 13 (n = 1029 patients) reported on return to baseline level of sports as an endpoint. The risk ratio (RR) of using BPTB vs HT on return to baseline sport level was 1.03 (0.91-1.17; P = .63). Absence of a positive pivot-shift test was the only secondary outcome, with a statistically significant RR of 0.66 (95% CI, 0.50-0.86) in favor of BPTB autografts (P = .002). Conclusion: In reviewing the current literature, no recommendation can be made on the optimal graft choice when using a return to baseline level of physical activity and/or sports participation as a primary metric.
Critical roles of cytokine storm and secondary bacterial infection in acute kidney injury development in COVID‐19: A multi‐center retrospective cohort study

Acute kidney injury (AKI) may develop in patients with coronavirus disease 2019 (COVID‐19) and is associated with in‐hospital death. We investigated the incidence of AKI in 223 hospitalized COVID‐19 patients and analyzed the influence factors of AKI. The incidence of cytokine storm syndrome and its correlation with other clinicopathologic variables were also investigated. We retrospectively enrolled adult patients with virologically confirmed COVID‐19 who were hospitalized at three hospitals in Wuhan and Guizhou, China between February 13, 2020, and April 8, 2020. We included 124 patients with moderate COVID‐19 and 99 with severe COVID‐19. AKI was present in 35 (15.7%) patients. The incidence of AKI was 30.3% for severe COVID‐19 and 4.0% for moderate COVID‐19 (p < 0.001). Furthermore, cytokine storm was found in 30 (13.5%) patients and only found in the severe group. Kidney injury at admission (odds ratio [OR]: 3.132, 95% confidence interval [CI]: 1.150–8.527; p = 0.025), cytokine storm (OR: 4.234, 95% CI: 1.361–13.171; p = 0.013), and acute respiratory distress syndrome (ARDS) (OR: 7.684, 95% CI: 2.622–22.523; p < 0.001) were influence factors of AKI. Seventeen (48.6%) patients who received invasive mechanical ventilation developed AKI, of whom 64.7% (11/17) died. Up to 86.7% of AKI patients with cytokine storms may develop a secondary bacterial infection. The leukocyte counts were significantly higher in AKI patients with cytokine storm than in those without (13.0 × 10⁹/L, interquartile range [IQR] 11.3 vs. 8.3 × 10⁹/L, IQR 7.5, p = 0.005). Approximately 1/6 patients with COVID‐19 eventually develop AKI. Kidney injury at admission, cytokine storm and ARDS are influence factors of AKI. Cytokine storm and secondary bacterial infections may be responsible for AKI development in COVID‐19 patients.
Radiomics and machine learning to predict aggressive type 2 endoleaks after endovascular aneurysm repair: a proof of concept

Background Persistent type 2 endoleaks (T2EL) require lifelong surveillance to avoid potentially life-threatening complications. Purpose To evaluate the performance of radiomic features (RF) derived from computed tomography angiography (CTA), for differentiating aggressive from benign T2ELs after endovascular aneurysm repair (EVAR). Material and Methods A prospective study was performed on patients who underwent EVAR from January 2018 to January 2020. Analysis was performed in patients who were diagnosed with T2EL based on the CTA of the first postoperative month and were followed at six months and one year. Patients were divided into two groups according to the change of aneurysm sac dimensions. Segmentation of T2ELs was performed and RF were extracted. Feature selection for subsequent machine-learning analysis was evaluated by means of artificial intelligence. Two support vector machines (SVM) classifiers were developed to predict the aneurysm sac dimension changes at one year, utilizing RF from T2EL at one- and six-month CTA scans, respectively. Results Among the 944 initial RF of T2EL, 58 and 51 robust RF from the one- and six-month CTA scans, respectively, were used for the machine-learning model development. The SVM classifier trained on one-month signatures was able to predict sac expansion at one year with an area under curve (AUC) of 89.3%, presenting 78.6% specificity and 100% sensitivity. Similarly, the SVM classifier developed with six-month radiomics data showed an AUC of 95.5%, specificity of 90.9%, and sensitivity of 100%. Conclusion Machine-learning algorithms utilizing CTA-derived RF may predict aggressive T2ELs leading to aneurysm sac expansion after EVAR.
Artificial intelligence in myopia: current and future trends

Purpose of review Myopia is one of the leading causes of visual impairment, with a projected increase in prevalence globally. One potential approach to address myopia and its complications is early detection and treatment. However, current healthcare systems may not be able to cope with the growing burden. Digital technological solutions such as artificial intelligence (AI) have emerged as a potential adjunct for myopia management. Recent findings There are currently four significant domains of AI in myopia, including machine learning (ML), deep learning (DL), genetics and natural language processing (NLP). ML has been demonstrated to be a useful adjunctive for myopia prediction and biometry for cataract surgery in highly myopic individuals. DL techniques, particularly convoluted neural networks, have been applied to various image-related diagnostic and predictive solutions. Applications of AI in genomics and NLP appear to be at a nascent stage. Summary Current AI research is mainly focused on disease classification and prediction in myopia. Through greater collaborative research, we envision AI will play an increasingly critical role in big data analysis by aggregating a greater variety of parameters including genomics and environmental factors. This may enable the development of generalizable adjunctive DL systems that could help realize predictive and individualized precision medicine for myopic patients.
Patients with patch test reactions associated with eye care products: Retrospective analysis of North American contact dermatitis group data, 2001‐2018

Department of Dermatology, Park Nicollet Health Services, Minneapolis, Minnesota, USA Department of Dermatology, University of Minnesota, Minneapolis, Minnesota, USA Department of Dermatology, Minneapolis Veterans Affairs Medical Center, Minneapolis, Minnesota, USA Medical School, University of Minnesota, Minneapolis, Minnesota, USA Division of Dermatology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada Department of Dermatology, Cleveland Clinic, Cleveland, Ohio, USA Department of Dermatology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA Division of Dermatology, University of Ottawa, Ottawa, Ontario, Canada Department of Dermatology, Duke University Medical Center, Durham, North Carolina, USA Division of Dermatology, CHU de Québec, Laval University, Québec, Québec, Canada Department of Dermatology, University of California San Francisco, San Francisco, California, USA Department of Dermatology, Columbia University Irving Medical School, New York, New York, USA Department of Dermatology, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA Department of Dermatology, University of Colorado, Boulder, Colorado, USA Department of Dermatology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA Division of Dermatology, Montreal General Hospital, McGill University, Montreal, Quebec, Canada Division of Dermatology, University of Louisville, Louisville, Kentucky, USA Department of Dermatology, Keck School of Medicine, Los Angeles, California, USA
Prevalence of Intimate Partner Violence Among the Maternal-Fetal Medicine Population

Intimate partner violence (IPV) is increasingly understood as an important public health issue. It is well understood that intimate partner violence has many negative effects on its survivors ranging from physical to mental health conditions. The population of people who experience intimate partner violence and population of pregnant women are both vulnerable populations. Examining the two populations together demands a trauma-informed approach and an understanding of the intricacies of both pregnancy and intimate partner violence. While IPV has been studied among the pregnant population, intimate partner violence as it relates to the maternal fetal medicine (MFM) or high-risk pregnancy population is not yet well understood. The purpose of this study is to describe the prevalence and effects of IPV among the MFM population at the Methodist Perinatal Center in Omaha, NE. This study analyzed secondary data obtained through the Abuse Assessment Screen (AAS) that was incorporated into the electronic medical record (EMR) at Methodist Perinatal Center. Data were input into SPSS from which descriptive statistics and a bivariate analysis (Chi square test) were entered. This study found that 5.6% of patients at Methodist Perinatal Center have experienced IPV. Further, this study found that seven maternal and fetal health outcomes are associated with IPV including: BMI ≥25, STI, psychiatric disorder, birth weight < 2.499kg, ultrasound anomaly, non-employer-based insurance (self-pay and Medicaid), and non-married status These results show that it is important to screen for IPV in the high-risk pregnancy setting. As this study shows that IPV occurs and negatively affects women and their children, there is a need for further research on the effects of IPV and development of interventions for the high-risk pregnant population.
Nanoscale Observation of the Electronic and Local Structures of LiCoO2 Thin Film Electrode by Depth-Resolved X-ray Absorption Spectroscopy

The electronic and local structural changes during electrochemical delithiation processes occurring at the electrode/electrolyte interface of LiCoO2 thin film electrode prepared by pulsed laser deposition were clarified by using depth-resolved X-ray absorption spectroscopy technique. We successfully obtained detailed microstructural information around the Li1–xCoO2 electrode surface with a depth resolution of ca. 3 nm using a spectro-electrochemical cell. Our results revealed a remarkable increase in the local distortions at the Li1–xCoO2 surface after charging, and the distortions extended to the bulk of Li1–xCoO2. Such unprecedented local distortions might be attributable to the marked deterioration of the electrodes.
REALIZATION OF INTERTEXTUALITY IN EDITORIALS OF PRESIDENTIAL ELECTION 2019

A text can be only interpreted through a background information of other text, and this is where intertextuality emerged, to shape another text. This study investigates the realization of intertextuality in articles of opposite editorials related to Presidential Election 2019. The objectives of the study is to evaluate the ways of the intertextuality realized. This research applied qualitative research design. The data were complex clauses which contained of intertextuality from opposite editorials of four newspapers, namely Kompas, Media Indonesia, Analisa, and Waspada started from January 2nd until April 17th 2019. The data were analyzed by using content analysis technique proposed by Elo and Kyngas (2007). The findings showed that; there were five elements those caused intertextuality realized in opposite editorials, they were; paraphrasing, patchwriting, making implicit meaning, putting contrastive conjunction, and last, image building
Influence of Korean professional male basketball players' characteristics on preventive health behaviors during COVID-19

Background and objective: The whole world is suffering extensive damage from COVID-19, and even the world of sports cannot escape this situation. Preventive behavior against COVID-19 is crucial to minimizing this damage. Therefore, this study analyzed data examining preventive behaviors of all Korean professional basketball players, providing empirical evidence of the relationship between preventive health behavior and Big-5 factors depending on socio-demographic variables. Material and methods: Using an online survey, data were collected from 106 players registered with the Korean Basketball League in the 2019-2020 season. Results: Married players and those with more years of experience were more thorough in managing injuries and preventing infections. Among the Big-5 personality traits, conscientiousness had a significant effect on COVID-19 prevention and health management behavior. Players low on neuroticism demonstrated higher performance in terms of injury management behavior. Conclusions: These results provide critical insight regarding the preventive health behavior of professional sports players. The findings can serve as basic data for enhancing COVID-19 preventive behavior ofmale basketball players, and as a reference for a decrease in damage in professional sports leagues from COVID-19 and normal management and maintenance.
Separating autotrophic and heterotrophic soil CO2 effluxes in afforested peatlands

Abstract. Peatlands are a significant global carbon (C) store, which can be compromised by drainage and afforestation. Quantifying the rate of C loss from peat soils under forestry is challenging, as soil CO2 efflux includes both CO2 produced from heterotrophic peat decomposition and CO2 produced by tree roots and associated fungal networks (autotrophic respiration). We experimentally terminated autotrophic belowground respiration in replicated forest plots by cutting through all living tree roots (trenching), and measured soil surface CO2 flux, litter input, litter decay rate and soil temperature and moisture over two years. Annual peat decomposition (heterotrophic CO2 flux) was 115 ± 16 g C m−2 y−1, representing c. 40 % of total soil respiration. Decomposition of needle litter is accelerated in the presence of an active rhizosphere, indicating a priming effects by labile C inputs from roots. This suggests that our estimates of peat mineralization in our trenched plots are conservative, and underestimate overall rates of peat C loss. Considering also input of litter from trees, our results indicate that the soils in these 30 year-old drained and afforested peatlands are a net sink for C, since substantially more C enters the soil as organic matter, than is decomposed heterotrophically. However, the C balance for these soils should be taken over the lifespan of the trees, in order to determine if the soils under these drained and afforested peatlands are a sustained sink of C, or become a net source over longer periods of forestry.
On Quantile Estimation and Mcmc Convergence

In this paper we examine the method of Raftery and Lewis (1992) for estimating the convergence of MCMC samplers, when functionals of interest are in the form of parameter quantiles. This method has proved to be one of the most popular methods for diagnosing convergence of MCMC algorithms. However, it is commonly mis-applied to problems where quantiles are not of primary interest. We show how the method can be misleading in this case, and that it can seriously underestimate the true length of the burn-in. We provide a number of examples, comparing the convergence rate of the chain in respect of a particular quantile, with that of the true convergence rate of the original chain. In particular we show how, in the case of the independence sampler, the two convergence rates are identical if the quantile of interest is chosen to be at an extreme of an appropriately reordered state space.
Semantic Boost on Episodic Associations : An Empirically-based Computational Model

Humans associate words remarkably easily and efficiently. Frequently the associations are formed incidentally and such associations provide a window into the cognitive structure of language networks and memory. How associations between words are formed, however, is not well understood. In a series of incidental associative learning experiments human participants associated semantically related but unassociated words easier than unrelated words. Furthermore, this advantage increased linearly as a function of the number of repeated co-occurrences of the word-pairs, up to a ceiling. In order to understand the mechanism of the semantic influence on word association processes a computational model, SEMANT, was developed. In this model, episodic associations are implemented by lateral connections that are formed between nodes in an already existing self-organized semantic map. These lateral connections are strengthened by each concomitant activation of two nodes in direct proportion with the amount of overlapping activity. Simulating associative learning with SEMANT replicated the empirical findings and led to two testable predictions. First, it should be easier to associate a word with few semantic neighbors to a word with many semantic neighbors than vice versa. Second, diffuse semantic activation, such as that characteristic to schizophrenic thought disorders, should reduce the advantage of associating semantically related pairs over unrelated pairs. The SEMANT model, therefore, suggests how the interaction of episodic and semantic memory can be understood in terms of specific neural computations.
SEISMIC PERFORMANCE COMPARISON OF TALL BUILDINGS WITH DUAL SYSTEM OF CONVENTIONAL AND BUCKLING RESTRAINED BRACED FRAMES

Following the recent construction technology improvements, a growing trend to build high-rise structures have been emerged. Due to specific characteristics of this type of structures, it is necessary to evaluate their seismic performance. In order to reduce the destructive effects of earthquakes, identification of a suitable lateral structural system is important. In this regards, dual system of “braced frames” and “special moment resistant frames” can be noted. Due to buckling of conventional bracing members under compressive load which causes reduction in energy absorption of this system, the buckling restrained braces have been proposed to improve seismic performance. In this paper, the seismic performance of moment resisting frames having special concentrically braces is compared with the performance of moment resisting frames having buckling restrained braces. For this purpose, two 30-story buildings with conventional and buckling restrained bracing system have been designed and modelled. Performance of the structures has been evaluated using incremental dynamic analysis (IDA) considering material and geometric nonlinearity. The results and the summary of the IDA curves and the fragility curves for two systems under the Immediate Occupancy (IO) and Collapse Prevention (CP) levels are presented. The results show that the conventional braces buckle under severe earthquake and the structure stiffness and its ability to absorb energy are reduced. It was also observed the buckling restrained braced frame has better performance compared to conventional braced frame and this type of system can be proposed as a desirable option in selecting a suitable system for high-rise buildings.
SEISMIC VULNERABILITY ASSESSMENT OF VICTORIA, BRITISH COLUMBIA, CANADA: IMPACT OF LONG DURATION SUBDUCTION ZONE GROUND MOTION

The City of Victoria, British Columbia, one of the oldest cities in Western Canada, has a current population of 80,000 people in just 19.5 km. The City of Victoria is located on the southern tip of Vancouver Island off Canada’s Pacific coast which happens to be in the Cascadia Subduction earthquake zone. Major subduction megathrust events and smaller, more frequent earthquakes can occur in the Cascadia Subduction zone, both of which pose a constant threat to the infrastructure and population of the city. The combination of a large, dense urban population, an aging building stock, and its location put Victoria at a high seismic risk. Accordingly, in 2017, the authors performed a seismic assessment for the City of Victoria in order to identify the city’s most atrisk buildings and to facilitate the development of a seismic resiliency plan. In this paper the results of the City of Victoria study, obtained using FEMA’s HAZUS framework, are compared to those obtained through the OpenQuake software. OpenQuake is a software package developed by Global Earthquake Model (GEM) for disaster risk reduction and combines probabilistic seismic hazard analysis with physical risk analysis to efficiently assess the seismic risk of a building or region. In this study, damage is calculated at a building-by-building level, based on a comprehensive database of building types, properties, and locations in Victoria. Results between the two frameworks are compared using individual building types and shaking levels, as well as general trends over large areas. Only damage probabilities are considered in this study; other loss metrics, such as cost or casualties are not considered, however, these measures are directly related to expected damage. HAZUS uses displacement-based structural fragility curves and obtains displacement estimates from static nonlinear analyses. The static nonlinear analysis procedure used in HAZUS can account for ground motion duration, as well as intensity. OpenQuake is a platform that allows the user to employ intensity-based fragility curves, which depend on the expected level of shaking. Part of this work was to compare the results of the two methodologies under moderate and long duration motions and to compare the differences in how they can account for ground motion duration. For this, the current fragility curves developed by GEM for use in OpenQuake for Canadian structures were employed.