Miracle-dz/UniFAR-FTUs huggingface dataset:
Unannounced versus announced hospital surveys: a nationwide cluster-randomized controlled trial

Abstract Objective To evaluate the effectiveness of unannounced versus announced surveys in detecting non-compliance with accreditation standards in public hospitals. Design A nationwide cluster-randomized controlled trial. Setting and participants All public hospitals in Denmark were invited. Twenty-three hospitals (77%) (3 university hospitals, 5 psychiatric hospitals and 15 general hospitals) agreed to participate. Intervention Twelve hospitals were randomized to receive unannounced surveys (intervention group) and eleven hospitals to receive announced surveys (control group). We hypothesized that the hospitals receiving the unannounced surveys would reveal a higher degree of non-compliance with accreditation standards than the hospitals receiving announced surveys. Nine surveyors trained and employed by the Danish Institute for Quality and Accreditation in Healthcare (IKAS) were randomized into teams and conducted all surveys. Main outcome measure The outcome was the surveyors’ assessment of the hospitals’ level of compliance with 113 performance indicators—an abbreviated set of the Danish Healthcare Quality Programme (DDKM) version 2, covering organizational standards, patient pathway standards and patient safety standards. Compliance with performance indicators was analyzed using binomial regression analysis with bootstrapped robust standard errors. Results In all, 16 202 measurements were acceptable for data analysis. The risk of observing non-compliance with performance indicators for the intervention group compared with the control group was statistically insignificant (risk difference (RD) = −0.6 percentage points [−2.51–1.31], P = 0.54). A converged analysis of the six patient safety critical standards, requiring 100% compliance to gain accreditation status revealed no statistically significant difference (RD = −0.78 percentage points [−4.01–2.44], P = 0.99). Conclusions Unannounced hospital surveys were not more effective than announced surveys in detecting quality problems in Danish hospitals. Trial Registration number ClinicalTrials.gov NCT02348567, https://clinicaltrials.gov/ct2/show/NCT02348567? term=NCT02348567.
DLLME-GC/ECD Method for the Residual Analysis of Parathion-Methyl and its Application in the Study of the UV-Photodegradation Process

A new method has been developed to determine trace levels of organophosphorus pesticide parathion-methyl in water samples by using dispersive liquid-liquid microextraction (DLLME), followed by gas chromatograph coupled with electron capture detector (GC/ECD) analysis. The optimized and validated method showed high extraction recovery (101.1%), high enrichment factor (57.3), low limits of detection and quantification, 0.083 and 0.250 μg L, respectively. The established DLLME-GC/ECD method has been successfully applied for the evaluation of the photodegradation of the parathion-methyl by UV254nm radiation in different conditions of pH and temperature. The parathion-methyl photodegradation at pH 3 and 35 °C achieved > 99.5% after 120 min of exposition. For this condition, it was observed the kinetic rate of 0.0515 min, the quantum yield of 1.22 × 10 mol Einstein and a half-life time of 13.46 min. All experimental conditions tested proved to be strongly influenced by pH and temperature. The application of the optimized process in distilled and drinking water spiked with parathion-methyl provided residues of this pesticide at levels below the maximum permitted by Brazilian legislation, which is 9.0 μg L.
Efficacy and safety of elotuzumab for the treatment of multiple myeloma

ABSTRACT Introduction: Multiple myeloma (MM) is the second most common hematologic malignancy and despite significant outcome improvements with novel agents, the majority of patients will eventually relapse and develop treatment resistance. Immunotherapy is emerging as a promising therapeutic approach in MM. Areas covered: Elotuzumab is a monoclonal antibody directly targeting the SLAMF7 receptor, expressed on normal and malignant plasma cells. Elotuzumab has no meaningful antimyeloma activity when given as monotherapy to patients with relapsed or refractory MM (RRMM). However, it demonstrated significant antimyeloma activity in preclinical studies and when it is combined with other antimyeloma agents (i.e. bortezomib or lenalidomide) in clinical trials, it improved response and clinical outcomes with no additive toxicity. This review provides a brief description of the elotuzumab mechanism of action and an overview on its efficacy in preclinical and clinical trials, including its safety and toxicity profile. Expert commentary: Based on the results of a phase 3 clinical trial (ELOQUENT-2), which compared lenalidomide and dexamethasone with or without elotuzumab in patients with RRMM, elotuzumab was approved by FDA in November 2015 for MM patients who received 1–3 prior lines of therapy. Studies with combinations of elotuzumab with other anti-myeloma drugs in different phases of MM are ongoing.
Synthesis and Characterization of Sol-Gel Prepared Silver Nanoparticles

Silver nanoparticles (SNPs) have been successfully prepared using sol–gel method by annealing the sample at 550°C for 30 min. The SNPs were not confirmed by X-ray diffraction (XRD) analysis when the annealing temperature was considered at 450°C. They were also not confirmed without calcination of the sample. The physical mechanism of silver clusters formation in the densified silica matrix with respect to thermal treatment has been understood. The presence of silver metal in the silica matrix was confirmed by XRD analysis and TEM image of the samples. The average size of nanoparticles dispersed in silica matrix was determined as 10.2 nm by the XRD technique. The synthesized nanocomposites were also characterized by UV-Visible spectroscopy with a peak in the absorption spectra at around 375 nm. The distribution of particle size has been reported here in the range from 8 nm to 25 nm by TEM observations of the sample prepared at 550°C. The spherically smaller size (≈10 nm) SNPs have reported the surface plasmons resonance (SPR) peak less than or near to 400 nm due to blue-shifting and effect of local refractive index. Without annealing the silica samples the absorption spectra does not show any peak around 375 nm. The FTIR spectroscopy of the three types of samples prepared at different temperatures (room temperature, 450°C and 550°C) has also been reported. This spectra have provided the identification of different chemical groups in the prepared samples. It has been predicted that the size of SNPs by XRD, UV-Visible and TEM results have agreed well with each other. It may be concluded that formation of SNPs is a function of annealing temperature.
A Phase II Randomized, Double‐Blind, Placebo‐Controlled Study of Simtuzumab or Placebo in Combination with Gemcitabine for the First‐Line Treatment of Pancreatic Adenocarcinoma

Abstract Lessons Learned. The safety profile in the gemcitabine/simtuzumab group was similar to that in the gemcitabine/placebo group. The addition of simtuzumab to gemcitabine does not improve clinical outcomes in patients with metastatic pancreatic adenocarcinoma Background. The humanized IgG4 monoclonal antibody simtuzumab inhibits the extracellular matrix‐remodeling enzyme lysyl oxidase‐like 2 maintaining pathological stroma in tumors. Methods. Adult patients with metastatic pancreatic adenocarcinoma (mPaCa) were randomly assigned to receive intravenous gemcitabine, 1,000 mg/m2, in combination with 200 or 700 mg simtuzumab or placebo. Primary endpoint was progression‐free survival (PFS), secondary endpoints included overall survival (OS), objective response rate (ORR), and safety. Results. Of 240 patients, 80 were randomly assigned to gemcitabine/simtuzumab 700 mg, 79 to gemcitabine/simtuzumab 200 mg, and 81 to gemcitabine/placebo. After a median follow‐up of 3.0, 1.9, and 3.4 months for gemcitabine/simtuzumab 700 mg, gemcitabine/simtuzumab 200 mg, and gemcitabine/placebo, respectively, the median PFS was 3.7 months (adjusted hazard ratio [HR], 95% confidence interval [CI], p value vs placebo: 1.09 [0.74–1.61]; p = .73), 3.5 months (1.13 [0.76–1.66], p = .61]), and 3.7 months, respectively. Median OS was 7.6 months (0.83 [0.57–1.22]; p = .28), 5.9 months (1.07 [0.73–1.55]; p = .69), and 5.7 months, respectively. ORRs were 13.9%, 14.5%, and 23.5%, respectively. Simtuzumab was well tolerated. Conclusion. The addition of simtuzumab to gemcitabine did not improve clinical outcomes in patients with mPaCa.
Model‐Based Approach to Predict Adherence to Protocol During Antiobesity Trials

Development of antiobesity drugs is continuously challenged by high dropout rates during clinical trials. The objective was to develop a population pharmacodynamic model that describes the temporal changes in body weight, considering disease progression, lifestyle intervention, and drug effects. Markov modeling (MM) was applied for quantification and characterization of responder and nonresponder as key drivers of dropout rates, to ultimately support the clinical trial simulations and the outcome in terms of trial adherence. Subjects (n = 4591) from 6 Contrave® trials were included in this analysis. An indirect‐response model developed by van Wart et al was used as a starting point. Inclusion of drug effect was dose driven using a population dose‐ and time‐dependent pharmacodynamic (DTPD) model. Additionally, a population‐pharmacokinetic parameter‐ and data (PPPD)‐driven model was developed using the final DTPD model structure and final parameter estimates from a previously developed population pharmacokinetic model based on available Contrave® pharmacokinetic concentrations. Last, MM was developed to predict transition rate probabilities among responder, nonresponder, and dropout states driven by the pharmacodynamic effect resulting from the DTPD or PPPD model. Covariates included in the models and parameters were diabetes mellitus and race. The linked DTPD‐MM and PPPD‐MM was able to predict transition rates among responder, nonresponder, and dropout states well. The analysis concluded that body‐weight change is an important factor influencing dropout rates, and the MM depicted that overall a DTPD model‐driven approach provides a reasonable prediction of clinical trial outcome probabilities similar to a pharmacokinetic‐driven approach.
Homeobox genes gain trimethylation of histone H3 lysine 4 in glioblastoma tissue

We revealed that in GBM homeobox genes gain tri-methylation on lysine 4 of histone H3 (H3K4me3), whereas the cell–cell adhesion-related cadherin genes lose H3K4me3, suggesting that the H3K4me3 alteration is related to the formation and migration of GBM cells.
Guaranteed error control bounds for the stabilised space-time IgA approximations to parabolic problems

The paper is concerned with space-time IgA approximations of parabolic initial-boundary value problems. We deduce guaranteed and fully computable error bounds adapted to special features of IgA approximations and investigate their applicability. The derivation method is based on the analysis of respective integral identities and purely functional arguments. Therefore, the estimates do not contain mesh-dependent constants and are valid for any approximation from the admissible (energy) class. In particular, they provide computable error bounds for norms associated with stabilised space-time IgA approximations as well as imply efficient error indicators enhancing the performance of fully adaptive solvers. The last section of the paper contains a series of numerical examples where approximate solutions are recovered by IgA techniques. The mesh refinement algorithm is governed by a local error indicator generated by the error majorant. Numerical results discussed in the last section illustrate both reliability, as well as the quantitative efficiency of the error estimates presented.
Understanding Error Propagation in Deep Learning Neural Network (DNN) Accelerators and Applications

Deep learning neural networks (DNNs) have been successful in solving a wide range of machine learning problems. Specialized hardware accelerators have been proposed to accelerate the execution of DNN algorithms for high-performance and energy efficiency. Recently, they have been deployed in datacenters (potentially for business-critical or industrial applications) and safety-critical systems such as self-driving cars. Soft errors caused by high-energy particles have been increasing in hardware systems, and these can lead to catastrophic failures in DNN systems. Traditional methods for building resilient systems, e.g., Triple Modular Redundancy (TMR), are agnostic of the DNN algorithm and the DNN accelerator’s architecture. Hence, these traditional resilience approaches incur high overheads, which makes them challenging to deploy. In this paper, we experimentally evaluate the resilience characteristics of DNN systems (i.e., DNN software running on specialized accelerators). We find that the error resilience of a DNN system depends on the data types, values, data reuses, and types of layers in the design. Based on our observations, we propose two efficient protection techniques for DNN systems.
Generative object detection and tracking in 3D range data

This paper presents a novel approach to tracking dynamic objects in 3D range data. Its key contribution lies in the generative object detection algorithm which allows the tracker to robustly extract objects of varying sizes and shapes from the observations. In contrast to tracking methods using discriminative detectors, we are thus able to generalize over a wide range of object classes matching our assumptions. Whilst the generative model underlying our framework inherently scales with the complexity and the noise characteristics of the environment, all parameters involved in the detection process obey a clean probabilistic interpretation. Nevertheless, our unsupervised object detection and tracking algorithm achieves real-time performance, even in highly dynamic scenarios covering a significant amount of moving objects. Through an application to populated urban settings, we are able to show that the tracking performance of the presented approach yields results which are comparable to state-of-the-art discriminative methods.
Minimal Hepatic Encephalopathy: The Reality Beyond Our Eyes.

INTRODUCTION Minimal hepatic encephalopathy refers to a mild neurocognitive impairment not detectable by clinical examination that can be present in cirrhotic patients. AIM To determine the prevalence of minimal hepatic encephalopathy in a secondary healthcare center in Northern Portugal. MATERIAL AND METHODS A cross-sectional study was conducted. Cirrhotic outpatients were included. EXCLUSION CRITERIA overt hepatic encephalopathy, illiteracy, active alcohol consumption, psychotropic drug use and therapy with lactulose. The presence of minimal hepatic encephalopathy was defined as a value ≥ -4 on the Psychometric Hepatic Encephalopathy Score, calculated according to the Portuguese norms. Variables analyzed: etiology and severity of liver disease and venous blood ammonia concentration. p values < 0.05 were considered significant. RESULTS From the 102 patients who were evaluated, 41 were included: 31 males, mean age 57 ± 10 years, mean education 5 ± 2 years, 31 in Child-Pugh class A, mean MELD score 6 ± 3. Minimal hepatic encephalopathy was diagnosed in 14 (34%) patients. The presence of minimal hepatic encephalopathy was unrelated to severity of liver disease. Despite being more elevated, the mean venous ammonia concentration in minimal hepatic encephalopathy patients was not statistically different from the mean venous ammonia concentration in non-minimal hepatic encephalopathy patients (48.5 ± 13.3 vs. 45.6 ± 15.6 μmol/L, p = 0.555). DISCUSSION The prevalence of minimal hepatic encephalopathy reported is in accordance with the international published data. CONCLUSION Minimal hepatic encephalopathy is a frequent condition that is present early in the course of cirrhosis, even in compensated cirrhotic patients. Therefore, this hidden entity should be actively pursued and managed properly.
Garment perception and its folding using a dual-arm robot

The work addresses the problem of clothing perception and manipulation by a two armed industrial robot aiming at a real-time automated folding of a piece of garment spread out on a flat surface. A complete solution combining vision sensing, garment segmentation and understanding, planning of the manipulation and its real execution on a robot is proposed. A new polygonal model of a garment is introduced. Fitting the model into a segmented garment contour is used to detect garment landmark points. It is shown how folded variants of the unfolded model can be derived automatically. Universality and usefulness of the model is demonstrated by its favorable performance within the whole folding procedure which is applicable to a variety of garments categories (towel, pants, shirt, etc.) and evaluated experimentally using the two armed robot. The principal novelty with respect to the state of the art is in the new garment polygonal model and its manipulation planning algorithm which leads to the speed up by two orders of magnitude.
Substrate effects in the photoenhanced ozonation of pyrene

Abstract. We report the effects of actinic illumination on the heterogeneous ozonation kinetics of solid pyrene films and pyrene adsorbed at air-octanol and air-aqueous interfaces. Upon illumination, the ozonation of solid pyrene films and pyrene at the air-aqueous interface proceeds more quickly than in darkness; no such enhancement is observed for pyrene at the air-octanol interface. Under dark conditions, the reaction of pyrene at all three interfaces proceeds via a Langmuir-Hinshelwood-type surface mechanism. In the presence of light, Langmuir-Hinshelwood kinetics are observed for solid pyrene films but a linear dependence upon gas-phase ozone concentration is observed at the air-aqueous interface. We interpret these results as evidence of the importance of charge-transfer pathways for the ozonation of excited-state pyrene. The dramatically different behaviour of pyrene at the surface of these three simple reaction environments highlights the difficulties inherent in representing complex reactive surfaces in the laboratory, and suggests caution in extrapolating laboratory results to environmental surfaces.
Split Sample Comparison of a Liquid-Based Method and Conventional Smears in Thyroid Fine Needle Aspiration

OBJECTIVE To compare the efficacy of the SurePath (SP) vs. conventional smears (CS) in fine needle aspiration (FNA) of thyroid gland lesions. STUDY DESIGN A total of 193 FNA cases with thyroid nodules were studied. Samples from ultrasound-guided FNA were split to prepare CS and SP slides. The diagnostic categories of unsatisfactory, benign, atypical and malignant were compared. Galectin-3 immunostaining was performed on SP slides. RESULTS Some differences were found between the cytomorphology of CS and SP. SP slides showed more increased cellularity and more clustered tissue fragments. On SP slides, nuclear detail and nucleoli were more easily detected and nuclear irregularity was very useful for the diagnosis of papillary carcinoma. SP showed a trend toward a lower proportion of atypical category. The overall sensitivity of FNA in diagnosing thyroid neoplasm was 90.9% for CS and 93.9% for SP. Most lesions (73%) diagnosed as papillary carcinoma after surgery showed positive staining of galectin-3. CONCLUSION The SP method showed easy evaluation of cytomorphologic features and consistent specimen quality and appeared to be more useful in diagnosing the suspicious cases. Moreover, it offered the possibility of adjunctive immunocytochemistry on the same sample.
A decentralized multi-agent unmanned aerial system to search, pick up, and relocate objects

We present a fully integrated autonomous multi­robot aerial system for finding and collecting moving and static objects with unknown locations. This task addresses multiple relevant problems in search and rescue (SAR) robotics such as multi-agent aerial exploration, object detection and tracking, and aerial gripping. Usually, the community tackles these problems individually but the integration into a working system generates extra complexity which is rarely addressed. We show that this task can be solved reliably using only simple components. Our decentralized system uses accurate global state estimation, reactive collision avoidance, and sweep plan­ning for multi-agent exploration. Objects are detected, tracked, and picked up using blob detection, inverse 3D-projection, Kalman filtering, visual-servoing, and a magnetic gripper. We evaluate the individual components of our system on the real platform. The full system has been deployed successfully in various public demonstrations, field tests, and the Mohamed Bin Zayed International Robotics Challenge 2017 (MBZIRC). Among the contestants we showed reliable performances and reached second place out of 17 in the individual challenge.
Study on Looseness and Impact - Rub Coupling Faults of a Vertical Dual-Disk Cantilever Rotor- Bearing System

Because of wrong setting or long-term running of rotating machinery, the looseness may ouur in the bearing seats or bases. And also bring impact and rubbing of rotor-stator, That is the looseness and rub-impact coupling fault. In the paper,a mechanics model and a finite element model of a vertical dual-disk cantilever rotor- bearing system with coupling faults of looseness and rub-impact are set up. Based on the nonlinear finite element method and contact theory, the dynamical characteristices of the system under the influence of the looseness rigidity and impact-rub clearance is studied. The results show that the impact-rub of rotor-stator can reduce the low frequency vibration caused by looseness, and the impact-rub caused by looseness has obvious orientation. Also, the conclusion of diagnosing the looseness and rub-impact coupling faults is given in the end of the paper.
Methylomic Analysis Identifies Frequent DNA Methylation of Zinc Finger Protein 582 (ZNF582) in Cervical Neoplasms

Background Despite of the trend that the application of DNA methylation as a biomarker for cancer detection is promising, clinically applicable genes are few. Therefore, we looked for novel hypermethylated genes for cervical cancer screening. Methods and Findings At the discovery phase, we analyzed the methylation profiles of human cervical carcinomas and normal cervixes by methylated DNA immunoprecipitation coupled to promoter tiling arrays (MeDIP-on-chip). Methylation-specific PCR (MSP), quantitative MSP and bisulfite sequencing were used to verify the methylation status in cancer tissues and cervical scrapings from patients with different severities. Immunohistochemical staining of a cervical tissue microarray was used to confirm protein expression. We narrowed to three candidate genes: DBC1, PDE8B, and ZNF582; their methylation frequencies in tumors were 93%, 29%, and 100%, respectively. At the pre-validation phase, the methylation frequency of DBC1 and ZNF582 in cervical scraping correlated significantly with disease severity in an independent cohort (n = 330, both P<0.001). For the detection of cervical intraepithelial neoplasia 3 (CIN3) and worse, the area under the receiver operating characteristic curve (AUC) of ZNF582 was 0.82 (95% confidence interval = 0.76–0.87). Conclusions Our study shows ZNF582 is frequently methylated in CIN3 and worse lesions, and it is demonstrated as a potential biomarker for the molecular screening of cervical cancer.