Miracle-dz/UniFAR-FTUs huggingface dataset:
Model predictive Controller for Mobile Robot

This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is implemented on a real robot. The comparison between a PID controller, adaptive controller, and the MPC illustrates advantage of the designed controller and its ability for exact control of the robot on a specified guide path.
Simplifying the spectral analysis of the volume operator

The volume operator plays a central role in both the kinematics and dynamics of canonical approaches to quantum gravity which are based on algebras of generalized Wilson loops. We introduce a method for simplifying its spectral analysis, for quantum states that can be realized on a cubic three-dimensional lattice. This involves a decomposition of Hilbert space into sectors transforming according to the irreducible representations of a subgroup of the cubic group. As an application, we determine the complete spectrum for a class of states with six-valent intersections. © 1997 Elsevier Science B.V. PACS: 04.60. Ds; 04.60. Nc; 02.20. Rt
Factors Associated with Human Immunodeficiency Virus First Line Treatment Failure in Zvishavane District, Zimbabwe, 2014

Introduction: Globally, first line HIV treatment failure remains a challenge, particularly in resource constrained settings. Midlands Province 2013 data showed that Zvishavane district had the highest prevalence of first line treatment failure at 16% against a national average of 1%. First line ART failure comes with poor treatment outcomes. We conducted a study to determine factors associated with first line HIV treatment failure in Zvishavane district. Methods: A 1:1 unmatched case control study was conducted. A case was an HIV positive patient who was on first line ART for >6 months in Zvishavane district and was switched to second line ART regimen because of treatment failure in 2013/2014. A control was an HIV patient in Zvishavane district who had been on first line ART for >6 months and had not failed first line ART. Pretested interviewer administered questionnaires were used to collect data from randomly selected participants. Logistic regression analysis was conducted. Results: A total of 246 participants, 123 cases and 123 controls, were recruited. Independent risk factors were poor adherence (<80% adherence) to ART [AOR=5.14, 95%CI (2.75-9.62)], drug stock outs [AOR=3.02, 95%CI (1.20- 6.98)], baseline CD4 count of <50 cells/mm3 [AOR=3.25, 95%CI (1.47-7.16)] and baseline WHO Stage 3 or 4 [AOR=1.95, 95%CI (1.05-3.61)]. Drug stock outs were a significant determinant of poor ART adherence [OR=3.09, 95%CI (1.83-5.21)]. Conclusion: Low baseline CD4 count and WHO stage 3 or 4 at ART initiation is associated with treatment failure. Improving adherence and avoiding ART drug stock outs may reduce treatment failure.
Hindrance demands as a boundary condition to the appraisal of challenge demands

ABSTRACT Background and objectives: Studies show that prototypical challenge demands can be appraised as challenging, hindering and threatening. Yet, to date there exists no clear reasoning as to why these different appraisals occur. Drawing on transactional stress theory, we propose that co-occurring hindrance demands likely affect the day-specific appraisal of challenge demands (i.e., time pressure and complexity). Design and method: To test this proposition we conducted a daily diary study with 432 employees. We tested our hypotheses using multi-level latent interaction analyses at the within-person level. Results: Results revealed that on days when individuals experienced more hindrance demands, they were less likely to appraise time pressure and complexity as challenging and more likely to appraise them as hindering or threatening. Conclusion: The results outline the need to consider co-occurring hindrance demands when assessing appraisal patterns associated with challenge demands.
Multistep loading of a DNA sliding clamp onto DNA by replication factor C

The DNA sliding clamp proliferating cell nuclear antigen (PCNA) is an essential co-factor for many eukaryotic DNA metabolic enzymes. PCNA is loaded around DNA by the ATP-dependent clamp loader replication factor C (RFC), which acts at single-stranded (ss)/double-stranded DNA (dsDNA) junctions harboring a recessed 3’ end (3’ ss/dsDNA junctions) and at DNA nicks. To illuminate the loading mechanism we have investigated the structure of RFC:PCNA bound to ATPγS and 3’ ss/dsDNA junctions or nicked DNA using cryogenic electron microscopy. Unexpectedly, we observe open and closed PCNA conformations in the RFC:PCNA:DNA complex, revealing that PCNA can adopt an open, planar conformation that allows direct insertion of dsDNA, and raising the question of whether PCNA ring closure is mechanistically coupled to ATP hydrolysis. By resolving multiple DNA-bound states of RFC:PCNA we observe that partial melting facilitates lateral insertion into the central channel formed by RFC:PCNA. We also resolve the Rfc1 N-terminal domain and demonstrate that its single BRCT domain participates in coordinating DNA prior to insertion into the central RFC channel, which promotes PCNA loading on the lagging strand of replication forks in vitro. Combined, our data suggest a comprehensive and fundamentally revised model for the RFC-catalyzed loading of PCNA onto DNA.
Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma.

PURPOSE To develop a novel multimodal data fusion model by incorporating computed tomography (CT) images and clinical variables based on deep learning for predicting the invasiveness risk of stage I lung adenocarcinoma that manifests as ground-glass nodules (GGNs), and compare the diagnostic performance of it with that of radiologists. METHODS A total of 1946 patients with solitary and histopathologically confirmed GGNs with maximum diameter less than 3 cm were retrospectively enrolled. The training dataset containing 1704 GGNs was augmented by resampling, scaling, random cropping, etc., to generate new training data. A multimodal data fusion model based on residual learning architecture and two multilayer perceptron with attention mechanism combining CT images with patient general data and serum tumor markers was built. The distance-based confidence scores (DCS) were calculated and compared among multimodal data models with different combinations. An observer study was conducted and the prediction performance of the fusion algorithms was compared with that of the two radiologists by an independent testing dataset with 242 GGNs. RESULTS Among the whole GGNs, 606 GGNs are confirmed as invasive adenocarcinoma (IA) and 1340 are non-IA. The proposed novel multimodal data fusion model combining CT images, patient general data and serum tumor markers achieved the highest accuracy (88.5%), Area under a ROC curve (AUC) (0.957), F1 (81.5%), F1weighted (81.9%) and Matthews correlation coefficient (MCC) (73.2%) for classifying between IA and non-IA GGNs, which was even better than the senior radiologist's performance (accuracy, 86.1%). In addition, the DCSs for multimodal data suggested that CT image had a stronger influence (0.9540) quantitatively than general data (0.6726) or tumor marker (0.6971). CONCLUSION This study demonstrated that the feasibility of integrating different types of data including CT images and clinical variables, and the multimodal data fusion model yielded higher performance for distinguishing IA from non-IA GGNs. This article is protected by copyright. All rights reserved.
PPISB: A Novel Network-Based Algorithm of Predicting Protein-Protein Interactions With Mixed Membership Stochastic Blockmodel

Protein-protein interactions (PPIs) play an essential role for most of biological processes in cells. Many computational algorithms have thus been proposed to predict PPIs. However, most of them heavily rest on the biological information of proteins while ignoring the latent structural features of proteins presented in a PPI network. In this paper, we propose an efficient network-based prediction algorithm, namely PPISB, based on a mixed membership stochastic blockmodel. By simulating the generative process of a PPI network, PPISB is able to capture the latent community structures. The inference procedure adopted by PPISB further optimizes the membership distributions of proteins over different complexes. After that, a distance measure is designed to compute the similarity between two proteins in terms of their likelihoods of being in the same complex, thus verifying whether they interact with each other or not. To evaluate the performance of PPISB, a series of extensive experiments have been conducted with five PPI networks collected from different species and the results demonstrate that PPISB has a promising performance when applied to predict PPIs in terms of several evaluation metrics. Hence, we reason that PPISB is preferred over state-of-the-art network-based prediction algorithms especially for predicting potential PPIs.
Live births with cerebral palsy at a tertiary maternity hospital: incidence and associated risk factors over a 17-year period

Abstract The aim of this retrospective study was to establish the incidence and associated risk factors for cerebral palsy (CP) at a tertiary maternity hospital in the UK between 2000–2016. We identified CP patients from our electronic coding system using ICD codes. Multiple independent variables for all live births born during this period were included in a univariate and multivariate logistic regression (LR) to identify associations between these and CP. We identified 130 CP children out of 87318 live births. Univariate LR determined male sex, birth weight <2500 g, gestational age of ≤36 weeks, Small-for-gestational-age, 1-and 5-minute Apgar score <9, neonatal intensive care unit (NICU) admission, multiple births, breech, emergency Caesarean section and delivery between 16.00–20.00 as significant risk factors. In the multivariate LG male sex, 1-minute Apgar <9, 5-minute Apgar <5 and admission to NICU remained as significant risk factors. The risk for delivery between 16.00–19.59 was nearly significant. There was a significant association between NICU admission and moderate-severe CP. Our CP incidence of 0.149% is at the lower end of the incidence spectrum of international comparisons. Impact Statement What is already known on this subject? The historic reported incidence of cerebral palsy (CP) ranges from 1.1 to 3.6 cases per 1000 live births, with birth weight <2500g, birth <28 weeks of gestation, Apgar scores ≤4 and male sex having been associated with an increased incidence. What do the results of this study add? This is a large series of live births from a tertiary maternity hospital with a comparative low CP incidence of 0.149%, despite the hospital dealing with many complex pregnancies and deliveries. We identified that already an Apgar score of <9 at 1 minute (significant) and births between 16.00–20.00 (non-significant) were associated with an increased risk to develop CP but not with a specific day of the week. What are the implications of these findings for clinical practice and/or future research? Our significant association between a 1-minute Apgar score of <9 and CP stresses the importance of immediate efficient resuscitation already for babies with a 1-minute score as high as 8. The increased CP risk for deliveries between 16.00–19.59 may be linked to staffing issues and needs further exploration. What this paper adds New data from a single maternity hospital Analysis of risk factors GMFCS distribution
Selected studies in the diagnosis of pulmonary embolism – review

The journal has had 7 points in Ministry of Science and Higher Education parametric evaluation. Part b item 1223 (26/01/2017). 1223 Journal of Education, Health and Sport eissn 2391-8306 7 © The Authors 2018; This article is published with open access at Licensee Open Journal Systems of Kazimierz Wielki University in Bydgoszcz, Poland Open Access. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author (s) and source are credited. This is an open access article licensed under the terms of the Creative Commons Attribution Non commercial license (Http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. This is an open access article licensed under the terms of the Creative Commons Attribution Non commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. The authors declare that there is no conflict of interests regarding the publication of this paper. Received: 05.02. 2018. Revised: 10.02. 2018. Accepted: 08.03. 2018.
High‐dimensional feature selection in competing risks modeling: A stable approach using a split‐and‐merge ensemble algorithm

Variable selection is critical in competing risks regression with high‐dimensional data. Although penalized variable selection methods and other machine learning‐based approaches have been developed, many of these methods often suffer from instability in practice. This paper proposes a novel method named Random Approximate Elastic Net (RAEN). Under the proportional subdistribution hazards model, RAEN provides a stable and generalizable solution to the large‐p‐small‐n variable selection problem for competing risks data. Our general framework allows the proposed algorithm to be applicable to other time‐to‐event regression models, including competing risks quantile regression and accelerated failure time models. We show that variable selection and parameter estimation improved markedly using the new computationally intensive algorithm through extensive simulations. A user‐friendly R package RAEN is developed for public use. We also apply our method to a cancer study to identify influential genes associated with the death or progression from bladder cancer.
Abdominal Organ Preservation Solutions in the Age of Machine Perfusion

The past decade has been the foreground for a radical revolution in the field of preservation in abdominal organ transplantation. Perfusion has increasingly replaced static cold storage as the preferred and even gold standard preservation method for marginal-quality organs. Perfusion is dynamic and offers several advantages in comparison with static cold storage. These include the ability to provide a continuous supply of new metabolic substrates, clear metabolic waste products, and perform some degree of organ viability assessment before actual transplantation in the recipient. At the same time, the ongoing importance of static cold storage cannot be overlooked, in particular when it comes to logistical and technical convenience and cost, not to mention the fact that it continues to work well for the majority of transplant allografts. The present review article provides an overview of the fundamental concepts of organ preservation, providing a brief history of static cold preservation and description of the principles behind and basic components of cold preservation solutions. An evaluation of current evidence supporting the use of different preservation solutions in abdominal organ transplantation is provided. As well, the range of solutions used for machine perfusion of abdominal organs is described, as are variations in their compositions related to changing metabolic needs paralleling the raising of the temperature of the perfusate from hypothermic to normothermic range. Finally, appraisal of new preservation solutions that are on the horizon is provided.
“I Could Never Tell My Parents”: Barriers to Queer Women's College Sexual Assault Disclosure to Family Members

Queer women are at high risk of college sexual victimization, but they face barriers to formal support services. As a result, informal support is critical. This study uses data from 40 open-ended interviews to explore family members’ reactions to queer women's disclosures and examine whether their family is a reliable source of informal support. Findings indicate that family reactions are often more harmful than helpful. In comparison to research focused on heterosexual survivors, we find family reactions to be more extreme and disparaging of queer survivors’ sexual identities. In fact, family members’ negative reactions may pose barriers to accessing formal services.
Novel Long-Chain Fatty Acid (LCFA)-Degrading Bacteria and Pathways in Anaerobic Digestion Promoted by Hydrochar as Revealed by Genome-Centric Metatranscriptomics Analysis

Long-chain fatty acids (LCFA) are difficult to be degraded in anaerobic digestion (AD), and the known LCFA degrading bacteria are only limited to the families Syntrophomonadaceae and Syntrophaceae. Here, we found that hydrochar effectively promoted AD of LCFA, and the new LCFA-degrading bacteria and a new metabolic pathway were also revealed based on genomic-centric metatranscriptomic analysis. ABSTRACT A large amount of long-chain fatty acids (LCFA) are generated after lipids hydrolysis in anaerobic digestion (AD), and LCFA are difficult to be biodegraded. This study showed that hydrochar (HC), which was produced during the hydrothermal liquefaction of organic wastes, significantly increased the methane production rate (by 56.9%) of oleate, a typical refractory model LCFA. Genomic-centric metatranscriptomics analysis revealed that three novel microbes (Bin138 Spirochaetota sp., Bin35 Smithellaceae sp., and Bin54 Desulfomonilia sp.) that were capable of degrading LCFA were enriched by HC, which played an important role in the degradation of oleate. LCFA was degraded to acetate through the well-known LCFA β-oxidation pathway and the combined β-oxidation and butyrate oxidation pathway. In addition, it was found that HC promoted the direct interspecies electron transfer (DIET) between Methanothrix sp. and Bin54 Desulfomonilia sp. The enriched new types of LCFA-degrading bacteria and the promotion of DIET contributed to the improved methane production rate of oleate by HC. IMPORTANCE Long-chain fatty acids (LCFA) are difficult to be degraded in anaerobic digestion (AD), and the known LCFA degrading bacteria are only limited to the families Syntrophomonadaceae and Syntrophaceae. Here, we found that hydrochar effectively promoted AD of LCFA, and the new LCFA-degrading bacteria and a new metabolic pathway were also revealed based on genomic-centric metatranscriptomic analysis. This study provided a new method for enhancing the AD of organic wastes with high content of LCFA and increased the understanding of the microbes and their metabolic pathways involved in AD of LCFA.
Estimating Vaccine Effectiveness from Linking Population-Based Health Registries: Some Sources of Bias

Abstract The COVID-19 pandemic has underscored the importance of observational studies of real-world vaccine effectiveness to help answer urgent public health questions. One approach to rapidly answering questions about real-world vaccine effectiveness relies on linking data from a population-based registry of vaccinations with a population-based registry of health outcomes. Here we consider some potential sources of bias in linked registry studies including: incomplete reporting to the registries; errors in linking individuals between registries; and errors in the assumed population size of the catchment area of the registries. We show that the direction of the bias resulting from one source of error by itself is predictable. However, if multiple sources of error are present, the direction of the bias can be either upward or downward. The biases can be so strong as to make harmful vaccines appear effective. We provide explicit formulas to quantify and adjust for multiple biases in estimates of vaccine effectiveness which could be used in sensitivity analyses. While this work was motivated by COVID-19 vaccine questions, the results are generally applicable to studies that link population-based exposure registries with population-based case registries to estimate relative risks of exposures.
From Kinetic Models to Hydrodynamics: Some Novel Results

1. Introduction. - 2. From the Phase Space to the Boltzmann Equation. - 3. Methods of Reduced Description. - 4. Hydrodynamic Spectrum of Simple Fluids. - 5. Hydrodynamic Fluctuations from the Boltzmann Equation. - 6. 13 Moment Grad System. - 7. Conclusions. - References.
Cytogenetic and epigenetic aberrations in peripheral lymphocytes of northwest Arkansas Marshallese

Abstract Purpose Nuclear weapons testing in the northern Marshall Islands between 1946 and 1958 resulted in ionizing radiation (IR) exposure of the thousands of Marshallese. Furthermore, numerous islands were contaminated by radioactive fallout. Significant increases in cancer and metabolic syndrome incidences have been reported among Marshallese, and potential for further increases looms due to the latency of radiation-induced health effects. The purpose of this study was to investigate the genetic and epigenetic effects of exposure to IR that could be associated with radiation-induced disease among the Northwest Arkansas (NWA) Marshallese. Materials and Methods We performed analysis of chromosomal aberrations and DNA methylation based on residential and exposure history of NWA Marshallese. Results Analysis of chromosomal aberrations demonstrated higher incidence of genetic rearrangements in women with self-reported history of radiation exposure (95% CI: 0.10, 1.22; p=.022). Further clustering of study participants based on their residential history demonstrated that participants who spent substantial amounts of time (≥6 months) in the northern atolls (thus, in the proximity of nuclear tests) before 1980 had more chromosomal aberrations than their peers who lived only in the southern atolls (95% CI: 0.08, −0.95; p=.021), and that this difference was driven by women. A relationship between the time spent in the northern atolls and increase in chromosomal aberrations was observed: 0.31 increase in chromosomal aberrations for every 10 years spent at northern atolls (95% CI: 0.06, 0.57; p=.020). Finally, significant inverse correlations between the chromosomal aberrations and the extent of DNA methylation of four LINE-1 elements L1PA2, L1PA16, L1PREC1, and L1P4B were identified. Conclusions The results of this study provide first evidence of the presence of stable genetic and epigenetic rearrangements in peripheral lymphocytes of NWA Marshallese and warrant further studies to analyze the role of radiation exposure in health disparities experienced by this Pacific Island nation.