Miracle-dz/UniFAR-FTUs huggingface dataset:
SIGLE: a valid procedure for Selective Inference with the Generalized Linear Lasso

This article investigates uncertainty quantification of the generalized linear lasso~(GLL), a popular variable selection method in high-dimensional regression settings. In many fields of study, researchers use data-driven methods to select a subset of variables that are most likely to be associated with a response variable. However, such variable selection methods can introduce bias and increase the likelihood of false positives, leading to incorrect conclusions. In this paper, we propose a post-selection inference framework that addresses these issues and allows for valid statistical inference after variable selection using GLL. We show that our method provides accurate $p$-values and confidence intervals, while maintaining high statistical power. In a second stage, we focus on the sparse logistic regression, a popular classifier in high-dimensional statistics. We show with extensive numerical simulations that SIGLE is more powerful than state-of-the-art PSI methods. SIGLE relies on a new method to sample states from the distribution of observations conditional on the selection event. This method is based on a simulated annealing strategy whose energy is given by the first order conditions of the logistic lasso.
Evolving Networks and Birth-and-Death Processes

Using a simple model with link removals as well as link additions, we show that an evolving network is scale free with a degree exponent in the range of (2, 4]. We then establish a relation between the network evolution and a set of non-homogeneous birth-and-death processes, and, with which, we capture the process by which the network connectivity evolves. We develop an effective algorithm to compute the network degree distribution accurately. Comparing analytical and numerical results with simulation, we identify some interesting network properties and verify the effectiveness of our method.
A Study of Diabetic Retinopathy Classification Using Support Vector Machine

Diabetic Retinopathy (DR) is a diabetic complication which can cause blindness. As DR cases keep increasing, ophthalmologists are forced to diagnose a large number of retinal images daily. Generally, the diabetic eye screening is done manually using qualitative scale to detect abnormalities on the retina. Although this approach is useful, the detection is not accurate; and create a need for a tool that can help the experts to classify the severity of DR to establish adequate therapy. Previous researchers have studied machine learning to pro-pose an automatic DR classification. However, it needs to be improvised especially in terms of accuracy. Hence, this paper aimed to find classifier with optimal performance in the study of DR classification. This study considered three classes of diabetic patients which were patients who do not have DR (NODR), patients with non-proliferative DR (NPDR) and patients with proliferative DR (PDR), instead of focusing only on two classes (NO DR, DR). Support Vector Machine was used in this research due to the success of many classification problems that had been proposed which produced good result. The results obtained showed that SVM gave the best accuracy, 76.62% with average sensitivity of 0.8081 and average specificity of 0.8376 respectively.
Implementing Agile Methodologies in a Project-Based Learning Laboratory

In this study, students at Engineering Dynamics, a distance-learning course offered to engineering technology students, were engaged in a design-based laboratory assignment. Teams of students from multiple campuses worked on design, manufacturing, and testing of a dynamic mechanism. Due to the cross-campus collaborative nature of this project and in the absence of little to no face-to-face interaction between team members, a key factor in success of the team was to manage team effort through an effective project management strategy. As a solution, ideas from agile way of thinking were incorporated in this design-based project. Agile rituals such as stand-up meetings, retrospectives and iterative reviews were implemented for transparent teamwork and timely feedback. The effectiveness of how this intervention helped students was assessed through multiple tools, such as online surveys and targeted design-based questions during mid-semester exams.
Effect of increasing zinc supplementation on post-transit performance, behavior, blood and muscle metabolites, and gene expression in growing beef feedlot steers

Abstract Fifty-four Angus-cross steers (297 kg ± 12) were stratified by body weight (BW) to pens (six steers per pen) to determine the effects of supplemental Zn on posttransit growth performance and blood and muscle metabolites. Dietary treatments started 25 d before trucking: control (CON; analyzed 54 mg Zn/kg DM), industry (IND; CON + 70 mg supplemental Zn/kg DM), and supranutritional Zn (SUPZN; CON + 120 mg supplemental Zn/kg DM). Supplemental Zn was bis-glycinate bound Zn (Plexomin Zn; Phytobiotics North America, Cary, NC). On day 0, steers were loaded onto a commercial trailer and transported in 18 h (1,822 km). Individual BW was recorded on days –26, –25, –1, and 0 (pre-transit), 1 (posttransit), 6, 27, and 28. Blood was collected on days –1, 1, 6, and 27. Longissimus thoracis biopsies were collected on days –1, 1, and 28. Daily individual feed disappearance was recorded via GrowSafe bunks. Data were analyzed using Proc Mixed of SAS with fixed effect of diet and steer as the experimental unit (growth performance, blood: n = 18 steers per treatment; muscle: n = 12 steers per treatment). Individual initial BW was used as a covariate in BW analysis. Contrast statements to test linear, quadratic, and Zn effects were used to analyze performance and blood parameters. Repeated measures analysis was used for posttransit DMI recovery and weekly posttransit DMI and Zn intake with the repeated effect of time. MetaboAnalyst 5.0 was utilized for statistical analysis of day 1 (off truck) muscle metabolites. Plasma Zn linearly increased due to Zn on days 1, 6, and 27 (P = 0.01), and off-truck (day 1) serum lactate increased over day –1 by 20%, 0%, and 20% in CON, IND, and SUPZN, respectively (Quadratic: P = 0.01). Muscle lactate tended to increase posttransit in CON and IND (P ≤ 0.07) but not SUPZN. Muscle metabolites relating to amino acid and nitrogen metabolism were increased in all treatments posttransit (P ≤ 0.02), and alanine-glucose cycle metabolites tended to increase in CON and IND (P ≤ 0.07). Steers supplemented with Zn recovered pretransit DMI quicker than CON (by d 2: P = 0.01), while IND had greater overall posttransit DMI than CON with SUPZN intermediate (P = 0.04), and Zn-fed steers had greater ADG posttransit (P = 0.04). Zinc supplementation mitigated muscle or serum lactate increases due to transit and increased posttransit ADG.
TP53 mutation detected in circulating exosomal DNA is associated with prognosis of patients with hepatocellular carcinoma

ABSTRACT Exosome DNA (exoDNA) can be used for liquid biopsy. This study was the first to use droplet digital PCR (ddPCR) to detect tumor-specific mutations in exoDNA and to evaluate the prognosis of hepatocellular carcinoma (HCC) patients. 60 HCC patients were enrolled in the study. We used ddPCR to detect c.747 G > T mutation in TP53 gene. We analyzed the correlation between detectable mutation in exoDNA and clinicopathologic characteristics using Multivariate logistics regression analysis. We performed Cox regression to assess the correlation between mutation frequency (mutant droplets/total droplets, MD/TD) and prognostic. We found that 48 of 60 patients had c.747 G > T mutation in TP53 gene in exoDNA (80.0%). We found that detectable mutation in exoDNA and age were associated with microvascular invasion (MVI) (P < .01). The ROC curve analysis revealed that the best cutoff value of mutation frequency to predict MVI was 67% (sensitivity 48.15%, specificity 93.94%,), the corresponding AUC was 0.761 (95%CI, 0.640–0.866; P < .01). Furthermore, we found that patients suffered high-frequency mutation (>67%) had shorted median recurrence-free survival (RFS) with 63 days (range, 53–202 days), compared with 368 days (range, 51–576 days) for patients with low-frequency mutation (<67%) (HR:4.61; 95% CI, 1.70–12.48; P = 0 .003). We also found that high-frequency mutation was associated with poor prognosis though patients had better pathological characteristics, such as AFP (<400 ng/mL), Liver cirrhosis (Negative), Tumor thrombus (Negative), Tumor numbers (Single) and Post-operation TACE (Executed). We provided evidence that the mutations in exoDNA might be used to predict patients with poor RFS. Abbreviations: TP53: Tumor protein p53; ExoDNA: Exosomal DNA; HCC: Hepatocellular carcinoma; ddPCR: Droplet digital Polymerase Chain Reaction (PCR); MD/TD: The ratio of mutant droplets/total droplets; AFP: Alpha-fetoprotein; MVI: Microvascular invasion; RFS: Recurrence-free survival.
Learning patient-centredness with simulated/standardized patients: A realist review: BEME Guide No. 68

Abstract Background Given the positive outcomes of patient-centred care on health outcomes, future doctors should learn how to deliver patient-centred care. The literature describes a wide variety of educational interventions with standardized patients (SPs) that focus on learning patient-centredness. However, it is unclear which mechanisms are responsible for learning patient-centredness when applying educational interventions with SPs. Objective This study aims to clarify how healthcare learners and professionals learn patient-centredness through interventions involving SPs in different healthcare educational contexts. Methods A realist approach was used to focus on what works, for whom, in what circumstances, in what respect and why. Databases were searched through 2019. Nineteen papers were included for analysis. Through inductive and deductive coding, CIC’MO configurations were identified to build partial program theories. These CIC’MOs describe how Interventions with SPs change the Context (C→C’) such that Mechanisms (M) are triggered that are expected to foster patient-centredness as Outcome. Results Interventions with SPs create three contexts which are ‘a safe learning environment,’ ‘reflective practice,’ and ‘enabling people to learn together. ’ These contexts trigger the following seven mechanisms: feeling confident, feeling a sense of comfort, feeling safe, self-reflection, awareness, comparing & contrasting perspectives, combining and broadening perspectives. A tentative final program theory with mechanisms belonging to three main learning components (cognitive, regulative metacognitive and affective) is proposed: Interventions with SPs create a safe learning environment (C’) in which learners gain feelings of confidence, comfort and safety (affective M). This safe learning environment enables two other mutual related contexts in which learners learn together (C’), through comparing & contrasting, combining and broadening their perspectives (cognitive M) and in which reflective practice (C’) facilitates self-reflection and awareness (metacognitive M) in order to learn patient-centeredness. Conclusion These insights offer educators ways to deliberately use interventions with SPs that trigger the described mechanisms for learning patient-centredness.
One-Node Quadrature Beats Monte Carlo: A Generalized Stochastic Simulation Algorithm

In conventional stochastic simulation algorithms, Monte Carlo integration and curve fitting are merged together and implemented by means of regression. We perform a decomposition of the solution error and show that regression does a good job in curve fitting but a poor job in integration, which leads to low accuracy of solutions. We propose a generalized notion of stochastic simulation approach in which integration and curve fitting are separated. We specifically allow for the use of deterministic (quadrature and monomial) integration methods which are more accurate than the conventional Monte Carlo method. We achieve accuracy of solutions that is orders of magnitude higher than that of the conventional stochastic simulation algorithms.
CRISPR/Cas‐based tools for the targeted control of plant viruses

Abstract Plant viruses are known to infect most economically important crops and pose a major threat to global food security. Currently, few resistant host phenotypes have been delineated, and while chemicals are used for crop protection against insect pests and bacterial or fungal diseases, these are inefficient against viral diseases. Genetic engineering emerged as a way of modifying the plant genome by introducing functional genes in plants to improve crop productivity under adverse environmental conditions. Recently, new breeding technologies, and in particular the exciting CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR‐associated proteins) technology, was shown to be a powerful alternative to engineer resistance against plant viruses, thus has great potential for reducing crop losses and improving plant productivity to directly contribute to food security. Indeed, it could circumvent the “Genetic modification” issues because it allows for genome editing without the integration of foreign DNA or RNA into the genome of the host plant, and it is simpler and more versatile than other new breeding technologies. In this review, we describe the predominant features of the major CRISPR/Cas systems and outline strategies for the delivery of CRISPR/Cas reagents to plant cells. We also provide an overview of recent advances that have engineered CRISPR/Cas‐based resistance against DNA and RNA viruses in plants through the targeted manipulation of either the viral genome or susceptibility factors of the host plant genome. Finally, we provide insight into the limitations and challenges that CRISPR/Cas technology currently faces and discuss a few alternative applications of the technology in virus research.
Steep increase in myopia among public school-going children in South India after COVID-19 home confinement

Purpose: Novel coronavirus has brought huge changes in lifestyle, especially among children. Reports indicate that the prevalence of refractive errors among children has increased due to home confinement. Hence, this study was done to understand the current status of refractive errors among children from public schools in southern India. Methods: This cross-sectional study was conducted as part of school eye screening conducted between September and October 2021. Children between 14 and 17 years of age from public schools underwent a three-phased comprehensive eye examination. Children identified with refractive errors and an equal proportion of children without any refractive errors underwent a survey on outdoor activities. Prevalence estimates and 95% confidence interval were calculated. Chi-square tests and regression analysis were used to understand the association between refractive error and other variables. Results: From the data of 3,850 (90.69%) children, the prevalence of vision impairment, refractive errors, and myopia in at least one eye was found to be 12.83% (n = 494), 21.51% (n = 828), and 19.53% (n = 752), respectively. The average myopic spherical equivalent error was found to be -2.17 ± 1.11D (range:-0.50 D to -14.00 D). Almost 96.82% of girls had less than 3 h of outdoor activities. Refractive errors were 7.42 and 2.77 times more (95% CI: 3.51-15.70), P < 0.001) among children who had outdoor activities less than 3 h per day and sleep less than 7 h per day. Conclusion: Comparing to previous studies from North Indian and South Indian public schools, this study reports a three- to six-fold rise in myopia post-home confinement among public school children from India.
Potential Protective Effects of Ruta Chalepensis L. Extracts Against Gentamicin-Induced Nephrotoxicity via Reduction on Apoptotic, DNA Damage and Oxidative Stress Markers in Mice

ABSTRACT In this study, the protective effects of Ruta chalepensis L. extracts on the extent of tissue damage in gentamicin-induced nephrotoxicity have been investigated. Ruta chalepensis L. extracts were prepared by subcritical water and ultrasound-assisted organic solvent extraction methods. Protective activity of Ruta chalepensis L. extracts on Gentamicin-induced nephrotoxicity is investigated by apoptotic, DNA damage, oxidative stress markers and evaluating histopathological in kidney tissue of mice. Gentamicin significantly increased Caspase-3 and −8 activities, NO levels, serum creatinine and BUN, while 8-OHdG and MDA levels were significantly decreased with Ruta chalepensis L. extract treatment. In addition, Ruta chalepensis L. extracts treatment significantly increased CAT and SOD activities. Histopathological alterations in Gentamicin group were significantly diminished by application of Ruta chalepensis L. extracts. These results suggest that treatment with Ruta chalepensis L. extracts may ameliorate renal dysfunction and structural damage through the reduction of oxidative stress and apoptosis in the kidney.
ALGORITHM OF REDUCTION

We show that the von Neumann’s algorithm of reduction (i.e. the algorithm of calculating the density matrix of the observable subsystem from the density matrix of the closed quantum system) corresponds to the special approximation at which the unobservable subsystem is supposed to be in the steady state of minimum information (infinite temperature) . We formulate the generalized algorithm of reduction that includes as limiting cases the von Neumann’s reduction and the selfcongruent correlated reduction most corresponding to the quantum nondemolition measurement. We demonstrate the correlation in dynamics of subsystems with exactly soluble models of quantum optics: 1) about the dynamics of a pair of interacting two-level atoms, and 2) about the dynamics of a two-level atom interacting with a single-mode resonant field.
Recent advances in erythrocyte membrane-camouflaged nanoparticles for the delivery of anti-cancer therapeutics

ABSTRACT Introduction Red blood cell (or erythrocyte) membrane-camouflaged nanoparticles (RBC-NPs) not only have a superior circulation life and do not induce accelerated blood clearance but also possess special functions, which offers great potential in cancer therapy. Areas covered This review focuses on the recent advances of RBC-NPs for delivering various agents to treat cancers in light of their vital role in improving drug delivery. Meanwhile, the construction and in vivo behavior of RBC-NPs are discussed to provide an in-depth understanding of the basis of RBC-NPs for improved cancer drug delivery. Expert opinion Although RBC-NPs are quite prospective in delivering anti-cancer therapeutics, they are still in their infancy stage and many challenges need to be overcome for successful translation into the clinic. The preparation and modification of RBC membranes, the optimization of coating methods, the scale-up production and the quality control of RBC-NPs, and the drug loading and release should be carefully considered in the clinical translation of RBC-NPs for cancer therapy.
Sensitivity and specificity of microRNA-204, CA125, and CA19.9 as biomarkers for diagnosis of ovarian cancer

Background Ovarian cancer is usually detected at later stages and no effective screening approach, has been identified. Therefore, sensitive and specific biomarkers for detecting ovarian cancer are urgently needed. Objective This study aimed to investigate the efficacy of six biomarkers for the early clinical diagnosis of ovarian cancer. Subjects & methods The study included 120 patients (benign ovarian tumors and early and late ovarian carcinoma) and 30 control healthy volunteers. MiRNA-204, CA125, CA19.9, hepcidin, microfibril-associated glycoprotein 2, and ferroportin levels were determined in all patients and control volunteers. Results The combined area under the receiver operating characteristic curves for miRNA-204, CA125, and CA19.9 were 0.938, 1.000, and 0.998 for benign tumors and early and late ovarian carcinomas, respectively. The sensitivities of miRNA-204, CA125, and CA19.9 were 98.04%, 100.00%, and 96.19% and the specificities were 58.33%, 62.50%, and 57.78%, respectively. Conclusion The positive predictivity of miRNA-204, CA125, and CA19.9 for ovarian cancer is high (59.57%, 58.24%, and 61.67%, respectively). Thus, the combination of these three biomarkers is a good diagnostic tool for ovarian cancer.
Conservation-form equations of unsteady open-channel flow

The unsteady open-channel flow equations are typically expressed in a variety of forms due to the imposition of differing assumptions, use of varied dependent variables, and inclusion of different source/sink terms. Questions often arise as to whether a particular equation set is expressed in a form consistent with the conservation-law definition. The concept of conservation form is developed to clarify the meaning mathematically. Six sets of unsteady-flow equations typically used in engineering practice are presented and their conservation properties are identified and discussed. Results of the theoretical development and analysis of the equations are substantiated in a set of numerical experiments conducted using alternate equation forms. Findings of these analytical and numerical efforts demonstrate that the choice of dependent variable is the fundamental factor determining the nature of the conservation properties of any particular equation form.
Does aquatic physical therapy affect the rehabilitation of breast cancer in women? A systematic review and meta-analysis of randomized controlled trials

To determine and evaluate the benefits of aquatic physical therapy as a rehabilitation strategy for women with breast cancer on health outcomes. Electronic databases including PubMed, Web of Science, Embase, Cochrane Library and China National Knowledge Infrastructure (CNKI), Weipu (VIP) and Wanfang database were systematically searched until June 2021. Randomized controlled trials were included if they evaluated the effects of aquatic physical therapy in breast cancer patients. The quality of the trials included was assessed by the two independent researchers according to the Cochrane Collaboration Handbook recommendations. Outcome measures were fatigue, waist circumference and quality of life (QoL). The study was registered under PROSPERO (CRD42021157323). Totally, five studies comprising 356 participants were included in the study. Meta-analyses showed that aquatic physical therapy interventions significantly reduced the fatigue score (MD = -2.14, 95%CI: -2.82, -1.45, p<0.01) compared with usual care; In addition, we also observed that, compared with land-based exercise, aquatic physical therapy greatly improved the QoL (MD = 2.85, 95%CI: 0.62, 5.09, p = 0.01). However, aquatic physical therapy cannot improve physical index (waist circumference) compared to usual care (MD = -3.49, 95%CI: -11.56,4.58, p = 0.4). Consequently, aquatic physical therapy had a positive effect on the fatigue and QoL. The results of this meta-analysis can provide a reliable evidence for evaluating the interventional effectiveness of aquatic physical therapy.