Miracle-dz/UniFAR-FTUs huggingface dataset:
The Unified Medical Language System at 30 Years and How It Is Used and Published: Systematic Review and Content Analysis

Background The Unified Medical Language System (UMLS) has been a critical tool in biomedical and health informatics, and the year 2021 marks its 30th anniversary. The UMLS brings together many broadly used vocabularies and standards in the biomedical field to facilitate interoperability among different computer systems and applications. Objective Despite its longevity, there is no comprehensive publication analysis of the use of the UMLS. Thus, this review and analysis is conducted to provide an overview of the UMLS and its use in English-language peer-reviewed publications, with the objective of providing a comprehensive understanding of how the UMLS has been used in English-language peer-reviewed publications over the last 30 years. Methods PubMed, ACM Digital Library, and the Nursing & Allied Health Database were used to search for studies. The primary search strategy was as follows: UMLS was used as a Medical Subject Headings term or a keyword or appeared in the title or abstract. Only English-language publications were considered. The publications were screened first, then coded and categorized iteratively, following the grounded theory. The review process followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Results A total of 943 publications were included in the final analysis. Moreover, 32 publications were categorized into 2 categories; hence the total number of publications before duplicates are removed is 975. After analysis and categorization of the publications, UMLS was found to be used in the following emerging themes or areas (the number of publications and their respective percentages are given in parentheses): natural language processing (230/975, 23.6%), information retrieval (125/975, 12.8%), terminology study (90/975, 9.2%), ontology and modeling (80/975, 8.2%), medical subdomains (76/975, 7.8%), other language studies (53/975, 5.4%), artificial intelligence tools and applications (46/975, 4.7%), patient care (35/975, 3.6%), data mining and knowledge discovery (25/975, 2.6%), medical education (20/975, 2.1%), degree-related theses (13/975, 1.3%), digital library (5/975, 0.5%), and the UMLS itself (150/975, 15.4%), as well as the UMLS for other purposes (27/975, 2.8%). Conclusions The UMLS has been used successfully in patient care, medical education, digital libraries, and software development, as originally planned, as well as in degree-related theses, the building of artificial intelligence tools, data mining and knowledge discovery, foundational work in methodology, and middle layers that may lead to advanced products. Natural language processing, the UMLS itself, and information retrieval are the 3 most common themes that emerged among the included publications. The results, although largely related to academia, demonstrate that UMLS achieves its intended uses successfully, in addition to achieving uses broadly beyond its original intentions.
Smart Prognostics and Health Management (SPHM) in Smart Manufacturing: An Interoperable Framework

Advances in the manufacturing industry have led to modern approaches such as Industry 4.0, Cyber-Physical Systems, Smart Manufacturing (SM) and Digital Twins. The traditional manufacturing architecture that consisted of hierarchical layers has evolved into a hierarchy-free network in which all the areas of a manufacturing enterprise are interconnected. The field devices on the shop floor generate large amounts of data that can be useful for maintenance planning. Prognostics and Health Management (PHM) approaches use this data and help us in fault detection and Remaining Useful Life (RUL) estimation. Although there is a significant amount of research primarily focused on tool wear prediction and Condition-Based Monitoring (CBM), there is not much importance given to the multiple facets of PHM. This paper conducts a review of PHM approaches, the current research trends and proposes a three-phased interoperable framework to implement Smart Prognostics and Health Management (SPHM). The uniqueness of SPHM lies in its framework, which makes it applicable to any manufacturing operation across the industry. The framework consists of three phases: Phase 1 consists of the shopfloor setup and data acquisition steps, Phase 2 describes steps to prepare and analyze the data and Phase 3 consists of modeling, predictions and deployment. The first two phases of SPHM are addressed in detail and an overview is provided for the third phase, which is a part of ongoing research. As a use-case, the first two phases of the SPHM framework are applied to data from a milling machine operation.
Bone-Marrow Stem Cells and Acellular Human Amniotic Membrane in a Rat Model of Heart Failure

Myocardial infarction (MI) remains the leading cause of cardiovascular death worldwide and a major cause of heart failure. Recent studies have suggested that cell-based therapies with bone marrow stem cells (BMSC) and human amniotic membrane (hAM) would recover the ventricular function after MI; however, the mechanisms underlying these effects are still controversial. Herein, we aimed to compare the effects of BMSC and hAM in a rat model of heart failure. MI was induced through coronary occlusion, and animals with an ejection fraction (EF) < 50% were included and randomized into three groups: control, BMSC, and hAM. The BMSC and hAM groups were implanted on the anterior ventricular wall seven days after MI, and a new echocardiographic analysis was performed on the 30th day, followed by euthanasia. The echocardiographic results after 30 days showed significant improvements on EF and left-ventricular end-sistolic and end-diastolic volumes in both BMSC and hAM groups, without significant benefits in the control group. New blood vessels, desmine-positive cells and connexin-43 expression were also elevated in both BMSC and hAM groups. These results suggest a recovery of global cardiac function with the therapeutic use of both BMSC and hAM, associated with angiogenesis and cardiomyocyte regeneration after 30 days.
Multiple Sensor Synchronization with theRealSense RGB-D Camera

When reconstructing a 3D object, it is difficult to obtain accurate 3D geometric information using a single camera. In order to capture detailed geometric information of a 3D object, it is inevitable to increase the number of cameras to capture the object. However, cameras need to be synchronized in order to simultaneously capture frames. If cameras are incorrectly synchronized, many artifacts are produced in the reconstructed 3D object. The RealSense RGB-D camera, which is commonly used for obtaining geometric information of a 3D object, provides synchronization modes to mitigate synchronization errors. However, the synchronization modes provided by theRealSense cameras can only sync depth cameras and have limitations in the number of cameras that can be synchronized using a single host due to the hardware issue of stable data transmission. Therefore, in this paper, we propose a novel synchronization method that synchronizes an arbitrary number of RealSense cameras by adjusting the number of hosts to support stable data transmission. Our method establishes a master–slave architecture in order to synchronize the system clocks of the hosts. While synchronizing the system clocks, delays that resulted from the process of synchronization were estimated so that the difference between the system clocks could be minimized. Through synchronization of the system clocks, cameras connected to the different hosts can be synchronized based on the timestamp of the data received by the hosts. Thus, our method synchronizes theRealSense cameras to simultaneously capture accurate 3D information of an object at a constant frame rate without dropping it.
Urban Intersection Classification: A Comparative Analysis

Understanding the scene in front of a vehicle is crucial for self-driving vehicles and Advanced Driver Assistance Systems, and in urban scenarios, intersection areas are one of the most critical, concentrating between 20% to 25% of road fatalities. This research presents a thorough investigation on the detection and classification of urban intersections as seen from onboard front-facing cameras. Different methodologies aimed at classifying intersection geometries have been assessed to provide a comprehensive evaluation of state-of-the-art techniques based on Deep Neural Network (DNN) approaches, including single-frame approaches and temporal integration schemes. A detailed analysis of most popular datasets previously used for the application together with a comparison with ad hoc recorded sequences revealed that the performances strongly depend on the field of view of the camera rather than other characteristics or temporal-integrating techniques. Due to the scarcity of training data, a new dataset is created by performing data augmentation from real-world data through a Generative Adversarial Network (GAN) to increase generalizability as well as to test the influence of data quality. Despite being in the relatively early stages, mainly due to the lack of intersection datasets oriented to the problem, an extensive experimental activity has been performed to analyze the individual performance of each proposed systems.
Ga Based Particles, Alloys and Composites: Fabrication and Applications

Liquid metal (LM) materials, including pure gallium (Ga) LM, eutectic alloys and their composites with organic polymers and inorganic nanoparticles, are cutting-edge functional materials owing to their outstanding electrical conductivity, thermal conductivity, extraordinary mechanical compliance, deformability and excellent biocompatibility. The unique properties of LM-based materials at room temperatures can overcome the drawbacks of the conventional electronic devices, particularly high thermal, electrical conductivities and their fluidic property, which would open tremendous opportunities for the fundamental research and practical applications of stretchable and wearable electronic devices. Therefore, research interest has been increasingly devoted to the fabrication methodologies of LM nanoparticles and their functional composites. In this review, we intend to present an overview of the state-of-art protocols for the synthesis of Ga-based materials, to introduce their potential applications in the fields ranging from wearable electronics, energy storage batteries and energy harvesting devices to bio-applications, and to discuss challenges and opportunities in future studies.
Oxidative Stress and Related Biomarkers in Gilbert’s Syndrome: A Secondary Analysis of Two Case-Control Studies

Bilirubin is an important antioxidant and a modulator of biological functions. However, most of the protection against oxidative stress was shown in vitro or ex vivo. The aim of this case-control study was to investigate whether subjects with Gilbert’s syndrome (GS) experience different levels of lipid and protein oxidation (as well as differences in oxidative stress related markers) compared to healthy controls. GS subjects (n = 119) demonstrated higher serum levels of unconjugated bilirubin (p < 0.001), a lower BMI (p < 0.001), 37% higher antioxidant potential assessed as ferric reducing ability potential (p < 0.001), higher advanced oxidation protein products (p < 0.01) andlower apolipoprotein B (p < 0.05), hs-C-reactive protein (p < 0.05), interleukin 6 (p < 0.001) and interleukin 1 beta (p < 0.05) values compared to healthy controls (n = 119). Furthermore, the resting heart rate was significantly lower in the GS group (p < 0.05). Stronger protective effects for GS subjects were demonstrated in the older subgroup (n = 104, average age 50 years) compared to those of the younger group (n = 134, average age 27 years). Although not all markers related to oxidative stress were different between the groups (e.g., malondialdehyde, homocysteine, oxLDL, and myeloperoxidase; p > 0.05), the observed differences contribute to the explanation of why GS serves as an important protector in the pathogenesis of metabolic, oxidative stress related diseases.
Fungal Biofilms as a Valuable Target for the Discovery of Natural Products That Cope with the Resistance of Medically Important Fungi—Latest Findings

The development of new antifungal agents that target biofilms is an urgent need. Natural products, mainly from the plant kingdom, represent an invaluable source of these entities. The present review provides an update (2017–May 2021) on the available information on essential oils, propolis, extracts from plants, algae, lichens and microorganisms, compounds from different natural sources and nanosystems containing natural products with the capacity to in vitro or in vivo modulate fungal biofilms. The search yielded 42 articles; seven involved essential oils, two Brazilian propolis, six plant extracts and one of each, extracts from lichens and algae/cyanobacteria. Twenty articles deal with the antibiofilm effect of pure natural compounds, with 10 of them including studies of the mechanism of action and five dealing with natural compounds included in nanosystems. Thirty-seven manuscripts evaluated Candida spp. biofilms and two tested Fusarium and Cryptococcus spp. Only one manuscript involved Aspergillus fumigatus. From the data presented here, it is clear that the search of natural products with activity against fungal biofilms has been a highly active area of research in recent years. However, it also reveals the necessity of deepening the studies by (i) evaluating the effect of natural products on biofilms formed by the newly emerged and worrisome health-care associated fungi, C. auris, as well as on other non-albicans Candida spp. , Cryptococcus sp. and filamentous fungi; (ii) elucidating the mechanisms of action of the most active natural products; (iii) increasing the in vivo testing.
Bacterial Community Analysis and Potential Functions of Core Taxa in Different Parts of the Fungus Cantharellus cibarius

Abstract Cantharellus cibarius is a widely distributed, popular, edible fungus with high nutritional and economic value. However, significant challenges persist in the microbial ecology and artificial cultivation of C. cibarius. Based on the 16S rRNA sequencing data, this study analyzed bacterial community structures and diversity of fruit bodies and rhizomorph parts of C. cibarius and mycosphere samples (collected in the Wudang District, Guiyang, Guizhou Province, China). It explored the composition and function of the core bacterial taxa. The analyzed results showed that the rhizomorph bacterial community structure was similar to mycosphere, but differed from the fruit bodies. Members of the Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium complex had the highest abundance in the fruit bodies. However, they were either absent or low in abundance in the rhizomorphs and mycosphere. At the same time, members of the Burkholderia-Caballeronia-Paraburkholderia complex were abundant in the fruit bodies and rhizomorphs parts of C. cibarius, as well as mycosphere. Through functional annotation of core bacterial taxa, we found that there was an apparent trend of potential functional differentiation of related bacterial communities in the fruit body and rhizomorph: potential functional groups of core bacterial taxa in the fruit bodies centered on nitrogen fixation, nitrogen metabolism, and degradation of aromatic compounds, while those in rhizomorphs focused on aerobic chemoheterotrophy, chemoheterotrophy, defense against soil pathogens, decomposition of complex organic compounds, and uptake of insoluble inorganic compounds. The analysis of functional groups of bacteria with different structures is of great significance to understand that bacteria promote the growth and development of C. cibarius.
Chemical, Nutritional and Sensory Characteristics of Six Ornamental Edible Flowers Species

Ornamental edible flowers can be used as novel nutraceutical sources with valuable biological properties. The purpose of this study was to establish nutritional, chemical, and sensory characteristics, antioxidant capacity (AC), and the relationship between their bioactive components and AC. The selected flowers Begonia × tuberhybrida, Tropaeolum majus, Calendula officinalis, Rosa, Hemerocallis, and Tagetes patula, can be easily collected due to their larger size. Their methanolic extracts were spectrophotometrically determined for polyphenols, flavonoids, and AC. Mineral elements were analyzed by atomic-absorption spectroscopy; crude protein was quantified by the Kjeldahl method. Eventually, 30 panelists evaluated sensory properties in 11 attributes. In addition, this study may serve to popularize selected blossoms. In flowers the contents of minerals were in this order: K > Ca > P > Mg > Na > Zn > Mn > Fe > Cu > Mo. AC ranged between 4.11 and 7.94 g of ascorbic acid equivalents/kg of fresh mass. The correlation coefficients between AC-total phenolics and AC-total flavonoids were r = 0.73* and r = 0.58*, respectively. It is also possible to observe a strong correlation between mineral elements and bioactive compounds. Hemerocallis was rated as the best and most tasteful; additionally, it exhibited the highest AC, total phenolic and flavonoid contents.
Response to Therapeutic Abortion in Lactating Dairy Cows Carrying Dead Twins during the Late Embryo/Early Fetal Period

Simple Summary The presence of dead embryos/fetuses can be precisely detected around 60 days post-insemination in dairy cattle. Little information on the fate of dead twins has been published. Practitioners usually apply a therapeutic abortion using prostaglandin F2α (PGF2α) or its analogs to reduce the associated extended interval to estrus. This study evaluated the dose–response effect of PGF2α inducing abortion in cows with two dead twins at pregnancy diagnosis 28–34 days post-AI (late embryonic period) or at confirmation of pregnancy 49–55 days post-AI (early fetal period). An increased PGF2α dose had no influence on the induction of abortion and the induced abortion rate was inversely associated with milk production during the late embryonic period, whereas an increased PGF2α dose was found to offer improvements during the early fetal period. Abstract This study examined the dose–response effect of prostaglandin F2α (PGF2α) when used to induce abortion in cows with two dead twins at pregnancy diagnosis 28–34 days post-AI (late embryonic period: LE) or at pregnancy confirmation 49–55 days post-AI (early fetal period: EF). The study population consisted of 415 cows receiving a single PGF2α dose (PG1 group: 254 LE and 161 EF cows) and 200 receiving a 1.5 × PGF2α dose (PG1.5 group: 121 LE and 79 EF cows). The induced abortion rate was significantly lower (chi-square test; p < 0.0001) in the EF (34.6%) than LE cows (88%), and was also reduced (p = 0.001) in the EF PG1 group (28%) compared with the EF PG1.5 group (48.1%). High milk production (≥45 kg) was the only factor influencing the induced abortion rate in LE cows (odds ratio 0.2; p < 0.0001), whereas the odds ratio for induced abortion of PG1.5 cows was 2.3 (p = 0.005) in EF cows. In conclusion, an increased PGF2α dose had no effect on abortion induction during the late embryonic period and its rate was inversely associated with milk production. This higher PGF2α dose did, however, offer benefits during the early fetal period.
Treatment Pattern of Antithrombotic Therapy over Time after Percutaneous Coronary Intervention in Patients with Atrial Fibrillation in Real-World Practice in Korea

We examined antithrombotic treatment patterns with clinical characteristics and therapy changes over time in patients with atrial fibrillation (AF) after percutaneous coronary intervention (PCI). Using the Health Insurance Review and Assessment service claims database (01JAN2007-30NOV2016) in Korea, we included adult patients with AF and PCI: (1) who underwent PCI with stenting between 01JAN2008 and 30NOV2016; (2) with ≥1 claim for AF (ICD code: I48) (3) with antithrombotics 1 day prior to or at the date of PCI; and (4) with CHADS2-VASc of ≥2. In this study, 7749 patients with AF who underwent PCI, triple therapy, dual therapy, dual antiplatelet therapy (DAPT), and single antiplatelet therapy were prescribed to 24.6%, 3.4%, 60.8%, and 11.0%, respectively. In the triple therapy group, 23.1% persisted with triple therapy for 12 months, whereas the remaining patients switched to a different therapy. In the entire cohort and several subgroups, the median treatment duration of triple therapy was 55–87 days. DAPT use for 12 months was the most common treatment pattern (62.6%) in the DAPT group (median treatment duration, 324–345 days). A significant discrepancy exists between the current guidelines and real-world practice regarding antithrombotic treatment with PCI for patients with AF. Appropriate use of anticoagulants should be emphasized.
Image Motion Extraction of Structures Using Computer Vision Techniques: A Comparative Study

Vibrational measurements play an important role for structural health monitoring, e.g., modal extraction and damage diagnosis. Moreover, conditions of civil structures can be mostly assessed by displacement responses. However, installing displacement transducers between the ground and floors in real-world buildings is unrealistic due to lack of reference points and structural scales and complexity. Alternatively, structural displacements can be acquired using computer vision-based motion extraction techniques. These extracted motions not only provide vibrational responses but are also useful for identifying the modal properties. In this study, three methods, including the optical flow with the Lucas–Kanade method, the digital image correlation (DIC) with bilinear interpolation, and the in-plane phase-based motion magnification using the Riesz pyramid, are introduced and experimentally verified using a four-story steel-frame building with a commercially available camera. First, the three displacement acquiring methods are introduced in detail. Next, the displacements are experimentally obtained from these methods and compared to those sensed from linear variable displacement transducers. Moreover, these displacement responses are converted into modal properties by system identification. As seen in the experimental results, the DIC method has the lowest average root mean squared error (RMSE) of 1.2371 mm among these three methods. Although the phase-based motion magnification method has a larger RMSE of 1.4132 mm due to variations in edge detection, this method is capable of providing full-field mode shapes over the building.