Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Basic Mechanics

DESCRIPTION OF PARTICLE MOTIONS. Length, Time, and Units. Displacements and Vectors. Velocity and Acceleration. Motion Along a Straight Line. Problem Solving. Curved Motion with Constant Acceleration. Circular and Relative Motions. MOTION AND INTERACTION OF PARTICLES. Newtonian Theory of Mechanics. Common Interactions. Problem Solving in Mechanics. More About Interactions. Kinetic Energy and Work. Potential Energy and the Energy Law. MOTION AND INTERACTION OF SYSTEMS. Momentum. Energy of a System. Rotational Motion. Angular-Momentum Law. Rolling and Equilibrium. Appendices.
A model independent measure of the large scale curvature of the Universe

Cosmological distances as a function of redshift depend on the effective curvature density via the effect on the geometrical path of photons from large scale spatial curvature and its effect on the expansion history, H(z). Cosmological time, however, depends on the expansion history only. Therefore, by combining distance and lookback time observations (or other estimates of the expansion history), it is possible to isolate the geometrical curvature contribution and measure the curvature in a model independent way, i.e., free from assumptions about the energy content of the universe. We investigate two different approaches to accomplish this task; the differential and the integral approach. The differential approach requires, in addition to distances, derivatives of distance with respect to redshift as well as knowledge of the expansion history. The integral approach is based on measuring the integral of the inverse of the expansion history via measurements of cosmic time as derived, e.g., from galaxy ages. In this paper, we attempt to constrain the large scale curvature of the Universe using distances obtained from observations of Type Ia supernovae together with inferred ages of passively evolving galaxies and Hubble parameter estimates from the large scale clustering of galaxies. Current data are consistent with zero spatial curvature, although the uncertainty on the curvature density is of order unity. Future data sets with on the order of thousands of Type Ia supernovae distances and galaxy ages will allow us to constrain the curvature density with an uncertainty of less than 0.1 at the 95% confidence level.
Experimental characterization and Monte Carlo simulation of scintillator detectors in online electron FLASH radiotherapy dosimetry

Radiotherapy (RT) is a fundamental tool in cancer treatment. Recent technological advances improved considerably radiotherapy techniques, allowing to obtain more precise, effective and most importantly safer treatments. However, RT is not without risks. Ionizing radiation also injures healthy cells, and there is a limit to the amount of radiation an area of the body can safely receive over the course of a lifetime. A new delivery method, called FLASH radiotherapy (FLASH-RT) has shown very promising results in in vivo studies, where a significant increase in healthy tissue sparing (FLASH effect) was observed. FLASH-RT consists in delivering the ionizing radiation therapy at dose rates much higher than the ones used in conventional radiotherapy (CONV-RT). Because of the novelty of this method, every aspect of FLASH-RT is under study, such as how the FLASH effect depends on therapy delivery parameters and what exactly are the underlining biological mechanisms. Nonetheless, dosimetry presents a challenge to overcome. The high dose rates cause significant saturation problems which render standard dosimetric equipment inadequate. Therefore, the development of online (active) dosimeters is a priority. In the short term this technology enables more efficient measurements in the experimental context, since it gives immediate feedback. In the long term it provides the basis for future studies on dosimetry in clinical practice. In this work we show the construction and characterization of online FLASH dosimeters based on scintillator materials used in integrating-mode. A GEANT4 based Monte Carlo simulation code is specifically developed to calculate the medium-equivalence correction. The simulation is validated with experimental measurements obtained with a full-fledged FLASH linear accelerator, which produces electron pulsed beams at very high dose per pulse. Measurements suggest that the proposed dosimeters have a linear response in a wide range of dose per pulse values up to 6 Gy/p, while moderate saturation can be observed up to 12.5 Gy/p.
A cross-platform smart drone controller framework – for real-time surveillance and inspection

This can form the basis for strategic management of new Smart Cities that aim to reduce Line-of-Sight piloting overheads and automate surveillance task. In this paper, we propose an architectural design to support the needed capabilities and basic features of a Smart Drone Controller. framework. This prototype framework supports a deployed team of Wi-Fi drones to conduct assigned surveillance. SDC’s machine learning engine evaluated with Deep Learning algorithms to detect target accuracy from drones live video feed. We have used Darknet/YOLO model for custom object detection in Intruder drone and Wall crack detection use cases and accuracy is reaching over 80%, which is encouraging.
Measurement of the t ¯ t Production Cross Section in p ¯ p collisions at √ s = 1 . 96 TeV using Lepton + Jets Events with Secondary Vertex b-tagging

We present a measurement of the t ¯ t production cross section using events with one charged lepton and jets from p ¯ p collisions at a center-of-mass energy of 1 . 96 TeV. In these events, heavy ﬂavor quarks from top quark decay are identiﬁed with a secondary vertex tagging algorithm. From 162 pb − 1 of data collected by the Collider Detector at Fermilab, a total of 48 candidate events are selected, where 13 . 5 ± 1 . 8 events are expected from background contributions. We measure a t ¯ t production cross section of 5 . 6 +1 . 2 − 1 . 1 (stat . ) +0 . 9 − 0 . 6 (syst . ) pb.
A systematic review and meta-analysis of thymic mucosa-associated lymphoid tissue lymphoma

Background Mucosa-associated lymphoid tissue (MALT) lymphoma of the thymus is a rare disease. The present meta-analysis aims at accumulating current evidence to explore the clinical characteristics, treatments, and prognoses of thymic MALT lymphoma. Methods We searched seven databases for studies published between the start date of database establishment and September 15, 2021. We included studies of patients with histological diagnoses and excluded those without data specifically on thymic MALT lymphoma. The quality was analyzed using an assessment tool. All data were tabulated. Pooled proportion was obtained using random-effects model. Statistical analysis was performed on R statistic software. Results Overall, 52 case reports and 13 case series were eligible. The quality of case reports was inferior to that of case series in terms of selection (P<0.001). Based on the analysis of patients in the case reports, age, gender, concurrent diseases, and tumor size did not differ between limited-stage and advanced-stage cases. Surgery is the mainstay to treat thymic MALT lymphoma. The surgical approach and extent did not influence the occurrence of events. Patients at Ann Arbor stage I were prone to not receiving postoperative therapy (P=0.011), though it may not reduce the occurrence of events (P=0.637). The five-year overall survival (OS) rate and five-year progression-free survival (PFS) rate were 97.2% and 88.4%, respectively. Patients with advanced-stage disease were more likely to suffer events (P=0.009). Conclusions Thymic MALT lymphoma is an extremely rare disease with a favorable prognosis. Currently available evidence is insufficient to draw solid judgments about treatment and prognosis. However, patients may benefit if thymectomy is chosen as the primary treatment. In some patients, lymph node sampling or dissection should be considered. In addition, if the patient is at an advanced-stage, postoperative therapy should be considered.
Trends and geographical variation in mortality from coronary disease in Peru

Background Coronary disease (CD) is the main cause of mortality worldwide. Data about trends and geographical variation in CD mortality is available in some American countries. This information varies among countries since CD risk factors frequencies vary. Objective To describe the trend and geographical variation of coronary disease (CD) mortality in Peru, 2005–2017. Methods Analysis of secondary data of the Peruvian Ministry of Health’s registry of deaths. We analyzed CD mortality. We described the absolute and relative frequency of deaths and age-standardized mortality rate (ASMR) by natural regions, departments, age, sex, and year. We also described the change of ASMR between two periods (2005–2010 vs. 2011–2017). Results There were 64,721 CD deaths between 2005 and 2017 (4.12% among all deaths). The absolute frequency of CD deaths was 5,665 and 6,565 in 2005 and 2017, respectively. CD mortality was more frequent in men and older adults. The ASMR varied among natural regions, being higher in the Coast (19.61 per 100,000 inhabitants). The change between the two periods revealed that almost all departments reduced their ASMRs, except for Callao, Lambayeque, and Madre de Dios. Conclusion CD mortality has increased in Peru. Mortality was higher in men and older adults, and it varied among departments. More political efforts are needed to reduce these trends.
MOCCA-College: Preliminary Validity Evidence of a Cognitive Diagnostic Reading Comprehension Assessment

As access to higher education increases, it is important to monitor students with special needs to facilitate the provision of appropriate resources and support. Although metrics such as the “reading readiness” ACT (formerly American College Testing) of provide insight into how many students may need such resources, they do not specify why a student may need support or how to provide that support. Increasingly, students are bringing reading comprehension struggles to college. Multiple-choice Online Causal Comprehension Assessment-College (MOCCA-College) is a new diagnostic reading comprehension assessment designed to identify who is a poor comprehender and also diagnose why they are a poor comprehender. Using reliability coefficients, receiver–operating characteristic curve analysis, and correlations, this study reports findings from the first year of a 3-year study to validate the assessment with 988 postsecondary students who took MOCCA-College, a subset of whom also provided data on other reading assessments (i.e., ACT, n = 377; Scholastic Aptitude Test [SAT], n = 192; and Nelson–Denny Reading Test [NDRT], n = 78). Despite some limitations (e.g., the sample is predominantly females from 4-year institutions), results indicate that MOCCA-College has good internal reliability, and scores are correlated with other reading assessments. Through a series of analyses of variance (ANOVAs), we also report how students identified by MOCCA-College as good and poor comprehenders differ in terms of demographics, cognitive processes used while reading, overall comprehension ability, and scores on admissions tests. Findings are discussed in terms of using MOCCA-College to help gauge which students may be at risk of reading comprehension difficulties, identify why they may be struggling, and inform directions in actionable instructional changes based on comprehension processing data.
Mental health in medical and biomedical doctoral students during the 2020 COVID-19 pandemic and racial protests

Concerns about the mental health of students, trainees and staff at universities and medical schools have been growing for many years. Recently, these have been exacerbated by the COVID-19 pandemic and a period of heightened reckoning and protests about systemic racism in the United States in 2020. To better understand the mental health of medical students and biomedical doctoral students at the University of North Carolina at Chapel Hill during this challenging period, we performed a cross-sectional study (n=957) using institutional annual survey data on measures of depression, anxiety, hazardous alcohol use, problems related to substance use, and suicidal ideation. These data were collected in 2019 and 2020, and were analyzed by type of training program, race/ethnicity, gender, sexual orientation, and survey year. Results indicated significant differences for rates of depression, anxiety, and suicidal ideation, with biomedical doctoral students showing greater incidence than medical students, and historically excluded students (e.g., people of color, women, LGBQ+ trainees) showing greater incidence compared to their peers. Of note, mental health remained poor for biomedical doctoral students in 2020 and declined for those belonging to historically excluded populations. The high rates of depression, anxiety, and suicidal ideation reported suggest that training environments need to be improved and support for mental health increased.
Visual assessment of interactions among resuscitation activity factors in out-of-hospital cardiopulmonary arrest using a machine learning model

Aim The evaluation of the effects of resuscitation activity factors on the outcome of out-of-hospital cardiopulmonary arrest (OHCA) requires consideration of the interactions among these factors. To improve OHCA success rates, this study assessed the prognostic interactions resulting from simultaneously modifying two prehospital factors using a trained machine learning model. Methods We enrolled 8274 OHCA patients resuscitated by emergency medical services (EMS) in Nara prefecture, Japan, with a unified activity protocol between January 2010 and December 2018; patients younger than 18 and those with noncardiogenic cardiopulmonary arrest were excluded. Next, a three-layer neural network model was constructed to predict the cerebral performance category score of 1 or 2 at one month based on 24 features of prehospital EMS activity. Using this model, we evaluated the prognostic impact of continuously and simultaneously varying the transport time and the defibrillation or drug-administration time in the test data based on heatmaps. Results The average class sensitivity of the prognostic model was more than 0.86, with a full area under the receiver operating characteristics curve of 0.94 (95% confidence interval of 0.92–0.96). By adjusting the two time factors simultaneously, a nonlinear interaction was obtained between the two adjustments, instead of a linear prediction of the outcome. Conclusion Modifications to the parameters using a machine-learning-based prognostic model indicated an interaction among the prognostic factors. These findings could be used to evaluate which factors should be prioritized to reduce time in the trained region of machine learning in order to improve EMS activities.
Efficacy and safety of intracoronary pro-urokinase injection during percutaneous coronary intervention in treating ST elevation myocardial infarction patients: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE Intracoronary injection of pro-urokinase (Pro-UK) during percutaneous coronary intervention (PCI) seems to be a promising treatment in improving myocardial perfusion. In this systematic review and meta-analysis, we aimed at investigating the efficacy and safety of intracoronary Pro-UK injection during PCI in ST elevation myocardial infarction (STEMI) patients. MATERIALS AND METHODS A comprehensive literature searched on PubMed, Embase, Cochrane, Ovid-MEDLINE, Ovid-Embase, Ovid-Cochrane Databases and ClinicalTrials.gov from inception until June 1, 2022, in English only. The primary outcome was myocardial perfusion, including thrombolysis in myocardial infarction (TIMI) grades, corrected TIMI frame count (CTFC), TIMI myocardial perfusion grades (TMPG). The secondary outcomes were ST-segment resolution (STR), major adverse cardiovascular events (MACE), myocardial marker, cardiac function and hemorrhagic complications. RESULTS We identified 5 studies (all RCTs) involving 761 participants. Under PCI procedure, compared with placebo, intracoronary Pro-UK injection may improve myocardial perfusion, including increasing the TIMI grades [odd ratio (OR) 0.46; 95% confidence interval (CI) 0.28-0.75; p = 0.002; I2 = 0%] , CTFC (OR -3.47; 95% CI [-5.60, -1.33]; p = 0.001; I2 = 0%) and TMPG (OR 0.17; 95% CI [0.06-0.44]; p = 0.0003; I2 = 0%), increase the rate of STR (OR 2.25; 95% CI [1.56-3.26]; p < 0.0001; I2 = 0%), reduce the incidence of MACE (OR 0.51; 95% CI [0.33-0.81]; p = 0.004; I2 = 0%) and reduce myocardial infarct size (CK, standardized mean difference [SMD] -0.45; 95% [CI] [-0.62, -0.28]; p < 0.00001; I2 = 10%. CK-MB, [SMD] -0.43; 95% CI [-0.68, -0.18]; p = 0.0007; I2 = 60%. cTnI, [SMD] -0.31; 95% CI [-0.46, -0.17]; p < 0.0001; I2 = 0%). Moreover, the treatment may improve the cardiac functions (LVFE, pooled mean difference [MD] 1.23; 95% CI [0.66-1.79]; p < 0.0001; I2 = 24%. LVEDd, pooled MD -0.13; 95% CI [-0.17, -0.09]; p < 0.00001; I2 = 0%). But there is no statistically significant difference between the Pro-UK group and placebo in the occurrence of hemorrhagic complications (OR 1.19; 95% CI [0.75-1.87]; p = 0.46; I2 = 0%). CONCLUSIONS Intracoronary Pro-UK injection during PCI in STEMI patients is an effective and safe treatment to perform. The treatment may improve myocardial perfusion and rate of STR, as well as decreasing the incidence of MACE and myocardial infarct size. Importantly, the treatment may improve the cardiac functions and life quality. In the future, more multi-centered and massive sample studies are required.
Divergent preferences for enhanced HIV testing options among high-risk populations in northern Tanzania: a short report

ABSTRACT To achieve the UNAIDS target of diagnosing 95% of all persons living with HIV, enhanced HIV testing services with greater attractional value need to be developed and implemented. We conducted a discrete choice experiment (DCE) to quantify preferences for enhanced HIV testing features across two high-risk populations in the Kilimanjaro Region in northern Tanzania. We designed and fielded a survey with 12 choice tasks to systematically recruited female barworkers and male mountain porters. Key enhanced features included: testing availability on every day of the week, an oral test, integration of a general health check or an examination for sexually transmitted infections (STI) with HIV testing, and provider-assisted confidential partner notification in the event of a positive HIV test result. Across 300 barworkers and 440 porters surveyed, mixed logit analyses of 17,760 choices indicated strong preferences for everyday testing availability, health checks, and STI examinations. Most participants were averse to oral testing and confidential partner notification by providers. Substantial preference heterogeneity was observed within each risk group. Enhancing HIV testing services to include options for everyday testing, general health checks, and STI examinations may increase the appeal of HIV testing offers to high-risk populations. Trial registration: ClinicalTrials.gov identifier: NCT02714140.
Szegő's Theorem and Its Descendants: Spectral Theory for L 2 Perturbations of Orthogonal Polynomials

This book presents a comprehensive overview of the sum rule approach to spectral analysis of orthogonal polynomials, which derives from Gabor Szego's classic 1915 theorem and its 1920 extension. Barry Simon emphasizes necessary and sufficient conditions, and provides mathematical background that until now has been available only in journals. Topics include background from the theory of meromorphic functions on hyperelliptic surfaces and the study of covering maps of the Riemann sphere with a finite number of slits removed. This allows for the first book-length treatment of orthogonal polynomials for measures supported on a finite number of intervals on the real line. In addition to the Szego and Killip-Simon theorems for orthogonal polynomials on the unit circle (OPUC) and orthogonal polynomials on the real line (OPRL), Simon covers Toda lattices, the moment problem, and Jacobi operators on the Bethe lattice. Recent work on applications of universality of the CD kernel to obtain detailed asymptotics on the fine structure of the zeros is also included. The book places special emphasis on OPRL, which makes it the essential companion volume to the author's earlier books on OPUC.
Homogeneous spaces and the Riccati equation in the calculus of variations

1. Classical Calculus of Variations. - 2. Riccati Equation in the Classical Calculus of Variations. - 3. Lie Groups and Lie Algebras. - 4. Grassmann Manifolds. - 5. Matrix Double Ratio. - 6. Complex Riccati Equations. - 7. Higher-Dimensional Calculus of Variations. - 8. On the Quadratic System of Partial Differential Equations Related to the Minimization Problem for a Multiple Integral. - Epilogue. - Appendix to the English Edition. - References.
Methylation levels assessment with Methylation-Sensitive High-Resolution Melting (MS-HRM)

Testing for disease-related DNA methylation changes provides clinically relevant information in personalized patient care. Methylation-Sensitive High-Resolution Melting (MS-HRM) is a method used for measuring methylation changes and has already been used in diagnostic settings. This method utilizes one set of primers that initiate the amplification of both methylated and non-methylated templates. Therefore, the quantification of the methylation levels using MS-HRM is hampered by the PCR bias phenomenon. Some approaches have been proposed to calculate the methylation level of samples using the high-resolution melting (HRM) curves. However, limitations of the methylation calculation using MS-HRM have not been evaluated systematically and comprehensively. We used the Area Under the Curve (AUC), a derivative of the HRM curves, and least square approximation (LSA) to establish a procedure that allowed us to infer methylation levels in an MS-HRM experiment and assess the limitations of that procedure for the assays’ specific methylation level measurement. The developed procedure allowed, with certain limitations, estimation of the methylation levels using HRM curves.
Data-Based and Opportunistic Integral Concurrent Learning for Adaptive Trajectory Tracking During Switched FES-Induced Biceps Curls

Hybrid exoskeletons, which combine functional electrical stimulation (FES) with a motorized testbed, can potentially improve the rehabilitation of people with movement disorders. However, hybrid exoskeletons have inherently nonlinear and uncertain dynamics, including combinations of discrete modes that switch between different continuous dynamic subsystems, which complicate closed-loop control. A particular complication is the uncertain muscle control effectiveness associated with FES. In this work, adaptive integral concurrent learning (ICL) motor and FES controllers are developed for a hybrid biceps curl exoskeleton, which are designed to achieve opportunistic and data-based learning of the uncertain human and electromechanical testbed parameters. Global exponential trajectory tracking and parameter estimation errors are proven through a Lyapunov-based stability analysis. The motor effectiveness is assumed to be unknown, and, to help with fatigue reduction, FES is enabled to switch between multiple electrodes on the biceps brachii, further complicating the analysis. A consequence of switching between the different uncertain subsystems is that the parameters must be opportunistically learned for each subsystem (i.e. each electrode and the motor), while that subsystem is active. Experiments were performed to validate the developed ICL controllers on twelve healthy participants. The average (± standard deviation) position tracking errors across each participant were 1.44 ± 5.32 deg, −0.25 ± 2.85 deg, and −0.17 ± 2.66 deg across biceps Curls 1-3, 4-7, and 8-10, respectively, where the average across the entire experiment was 0.28 ± 3.53 deg.