Miracle-dz/UniFAR-FTUs huggingface dataset:
Mira: A Framework for Static Performance Analysis

The performance model of an application can provide understanding about its runtime behavior on particular hardware. Such information can be analyzed by developers for performance tuning. However, model building and analyzing is frequently ignored during software development until performance problems arise because they require significant expertise and can involve many time-consuming application runs. In this paper, we propose a fast, accurate, flexible and user-friendly tool, Mira, for generating performance models by applying static program analysis, targeting scientific applications running on supercomputers. We parse both the source code and binary to estimate performance attributes with better accuracy than considering just source or just binary code. Because our analysis is static, the target program does not need to be executed on the target architecture, which enables users to perform analysis on available machines instead of conducting expensive experiments on potentially expensive resources. Moreover, statically generated models enable performance prediction on nonexistent or unavailable architectures. In addition to flexibility, because model generation time is significantly reduced compared to dynamic analysis approaches, our method is suitable for rapid application performance analysis and improvement. We present empirical validation results to demonstrate the current capabilities of our approach on small benchmarks and a mini application.
Symmetry matched auditory cues improve gait steadiness in most people with Parkinson's disease but not in healthy older people.

BACKGROUND Unsteady gait and falls are major problems for people with Parkinson's disease (PD). Symmetric auditory cues at altered cadences have been used to improve walking speed or step length. However, few people are exactly symmetric in terms of morphology or movement patterns and effects of symmetric cueing on gait steadiness are inconclusive. OBJECTIVES To investigate if matching auditory cue a/symmetry to an individual's intrinsic symmetry or asymmetry affects gait steadiness, gait symmetry, and comfort to cues, in people with PD, healthy age-matched controls (HAM) and young. METHODS Thirty participants; 10 with PD, 11 HAM (66 years), and 9 young (30 years), completed five baseline walks (no cues) and twenty-five cued walks at habitual cadence but different a/symmetries. Outcomes included; gait steadiness (step time variability and smoothness by harmonic ratios), walking speed, symmetry, comfort, and cue lag times. RESULTS Without cues, PD participants had slower and less steady gait than HAM or young. Gait symmetry was distinct from gait steadiness, and unaffected by cue symmetry or a diagnosis of PD, but associated with aging. All participants maintained preferred gait symmetry and lag times independent of cue symmetry. When cues were matched to the individual's habitual gait symmetry and cadence: Gait steadiness improved in the PD group, but deteriorated in the HAM controls, and was unchanged in the young. Gait outcomes worsened for the two PD participants who reported discomfort to cued walking and had high New Freezing of Gait scores. CONCLUSIONS It cannot be assumed all individuals benefit equally from auditory cues. Symmetry matched auditory cues compensated for unsteady gait in most people with PD, but interfered with gait steadiness in older people without basal ganglia deficits.
High Prevalence of Quorum-Sensing and Quorum-Quenching Activity among Cultivable Bacteria and Metagenomic Sequences in the Mediterranean Sea

There is increasing evidence being accumulated regarding the importance of N-acyl homoserine lactones (AHL)-mediated quorum-sensing (QS) and quorum-quenching (QQ) processes in the marine environment, but in most cases, data has been obtained from specific microhabitats, and subsequently little is known regarding these activities in free-living marine bacteria. The QS and QQ activities among 605 bacterial isolates obtained at 90 and 2000 m depths in the Mediterranean Sea were analyzed. Additionally, putative QS and QQ sequences were searched in metagenomic data obtained at different depths (15–2000 m) at the same sampling site. The number of AHL producers was higher in the 90 m sample (37.66%) than in the 2000 m sample (4.01%). However, the presence of QQ enzymatic activity was 1.63-fold higher in the 2000 m sample. The analysis of putative QQ enzymes in the metagenomes supports the relevance of QQ processes in the deepest samples, found in cultivable bacteria. Despite the unavoidable biases in the cultivation methods and biosensor assays and the possible promiscuous activity of the QQ enzymes retrieved in the metagenomic analysis, the results indicate that AHL-related QS and QQ processes could be common activity in the marine environment.
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

Estimating the 6D pose of known objects is important for robots to interact with the real world. The problem is challenging due to the variety of objects as well as the complexity of a scene caused by clutter and occlusions between objects. In this work, we introduce PoseCNN, a new Convolutional Neural Network for 6D object pose estimation. PoseCNN estimates the 3D translation of an object by localizing its center in the image and predicting its distance from the camera. The 3D rotation of the object is estimated by regressing to a quaternion representation. We also introduce a novel loss function that enables PoseCNN to handle symmetric objects. In addition, we contribute a large scale video dataset for 6D object pose estimation named the YCB-Video dataset. Our dataset provides accurate 6D poses of 21 objects from the YCB dataset observed in 92 videos with 133,827 frames. We conduct extensive experiments on our YCB-Video dataset and the OccludedLINEMOD dataset to show that PoseCNN is highly robust to occlusions, can handle symmetric objects, and provide accurate pose estimation using only color images as input. When using depth data to further refine the poses, our approach achieves state-of-the-art results on the challenging OccludedLINEMOD dataset. Our code and dataset are available at this https URL.
Stochastic Pharmacokinetic-Pharmacodynamic Modeling for Assessing the Systemic Health Risk of Perfluorooctanoate (PFOA)

Abstract A phase 1 dose-escalation trial assessed the chemotherapeutic potential of ammonium perfluorooctanoate (APFO). Forty-nine primarily solid-tumor cancer patients who failed standard therapy received weekly APFO doses (50–1200 mg) for 6 weeks. Clinical chemistries and plasma PFOA (anionic APFO) were measured predose and weekly thereafter. Several clinical measures including total cholesterol, high-density lipoproteins (HDLs), thyroid stimulating hormone (TSH), and free thyroxine (fT4), relative to PFOA concentrations were examined by: Standard statistical analyses using generalized estimating equations (GEE) and a probabilistic analysis using probability distribution functions (pdf) at various PFOA concentrations; and a 2-compartment pharmacokinetic/pharmacodynamic (PK/PD) model to directly estimate mean changes. Based on the GEE, the average rates of change in total cholesterol and fT4 associated with increasing PFOA were approximately −1.2×10−3 mmol/l/μM and 2.8×10−3 pmol/l/μM, respectively. The PK/PD model predicted more closely the trends observed in the data as well as the pdfs of biomarkers. A decline in total cholesterol was observed, with a clear transition in shape and range of the pdfs, manifested by the maximum value of the Kullback-Leibler (KL) divergence, that occurred at plasma PFOA between 420 and 565 μM (175 000–230 000 ng/ml). High-density lipoprotein was unchanged. An increase in fT4 was observed at a higher PFOA transition point, albeit TSH was unchanged. Our findings are consistent with some animal models and may motivate re-examination of the epidemiologic studies to PFOA at levels several orders of magnitude lower than this study. These observational studies have reported contrary associations, but currently understood biology does not support the existence of such conflicting effects.
Increased activity of the orexin system in the paraventricular nucleus contributes to salt-sensitive hypertension.

The orexin system is involved in arginine vasopressin (AVP) regulation, and its overactivation has been implicated in hypertension. However, its role in salt-sensitive hypertension (SSHTN) is unknown. Here, we tested the hypothesis that hyperactivity of the orexin system in the paraventricular nucleus (PVN) contributes to SSHTN via enhancing AVP signaling. Eight-week-old male Dahl salt-sensitive (Dahl S) and age- and sex-matched Sprague-Dawley (SD) rats were placed on a high-salt (HS; 8% NaCl) or normal-salt (NS; 0.4% NaCl) diet for 4 wk. HS intake did not alter mean arterial pressure (MAP), PVN mRNA levels of orexin receptor 1 (OX1R), or OX2R but slightly increased PVN AVP mRNA expression in SD rats. HS diet induced significant increases in MAP and PVN mRNA levels of OX1R, OX2R, and AVP in Dahl S rats. Intracerebroventricular infusion of orexin A (0.2 nmol) dramatically increased AVP mRNA levels and immunoreactivity in the PVN of SD rats. Incubation of cultured hypothalamus neurons from newborn SD rats with orexin A increased AVP mRNA expression, which was attenuated by OX1R blockade. In addition, increased cerebrospinal fluid Na+ concentration through intracerebroventricular infusion of NaCl solution (4 µmol) increased PVN OX1R and AVP mRNA levels and immunoreactivity in SD rats. Furthermore, bilateral PVN microinjection of the OX1R antagonist SB-408124 resulted in a greater reduction in MAP in HS intake (-16 ± 5 mmHg) compared with NS-fed (-4 ± 4 mmHg) anesthetized Dahl S rats. These results suggest that elevated PVN OX1R activation may contribute to SSHTN by enhancing AVP signaling.NEW & NOTEWORTHY To our best knowledge, this study is the first to investigate the involvement of the orexin system in salt-sensitive hypertension. Our results suggest that the orexin system may contribute to the Dahl model of salt-sensitive hypertension by enhancing vasopressin signaling in the hypothalamic paraventricular nucleus.
A Pilot Medical Curriculum Analysis and Visualization According to Medbiquitous Standards

Curriculum design and implementation in higher medical education can be a great challenge. Although there are well-defined standards, such as the Curriculum Inventory and Competency Framework by MedBiquitous Consortium, existing systems are incapable of a visual representation of the various components, attributes, and relations. In this paper, we present the MEDCIN platform, a pilot tool which uses a standard-compliant curriculum data model to offer comprehensive and thorough analysis of a given curriculum. In addition, the ongoing research in challenging areas, such as the curriculum content comparison, can reveal valuable knowledge from existing data and transform the future of medical education.
Effect of Strategy Adaptation on Differential Evolution in Presence and Absence of Parameter Adaptation: An Investigation

Abstract Differential Evolution (DE) is a simple, yet highly competitive real parameter optimizer in the family of evolutionary algorithms. A significant contribution of its robust performance is attributed to its control parameters, and mutation strategy employed, proper settings of which, generally lead to good solutions. Finding the best parameters for a given problem through the trial and error method is time consuming, and sometimes impractical. This calls for the development of adaptive parameter control mechanisms. In this work, we investigate the impact and efficacy of adapting mutation strategies with or without adapting the control parameters, and report the plausibility of this scheme. Backed with empirical evidence from this and previous works, we first build a case for strategy adaptation in the presence as well as in the absence of parameter adaptation. Afterwards, we propose a new mutation strategy, and an adaptive variant SA-SHADE which is based on a recently proposed self-adaptive memory based variant of Differential evolution, SHADE. We report the performance of SA-SHADE on 28 benchmark functions of varying complexity, and compare it with the classic DE algorithm (DE/Rand/1/bin), and other state-of-the-art adaptive DE variants including CoDE, EPSDE, JADE, and SHADE itself. Our results show that adaptation of mutation strategy improves the performance of DE in both presence, and absence of control parameter adaptation, and should thus be employed frequently.
Nurses' Attitudes Toward the Use of the Bar-coding Medication Administration System

This study determines nurses' attitudes toward bar-coding medication administration system use. Some of the factors underlying the successful use of bar-coding medication administration systems that are viewed as a connotative indicator of users' attitudes were used to gather data that describe the attitudinal basis for system adoption and use decisions in terms of subjective satisfaction. Only 67 nurses in the United States had the chance to respond to the e-questionnaire posted on the CARING list server for the months of June and July 2007. Participants rated their satisfaction with bar-coding medication administration system use based on system functionality, usability, and its positive/negative impact on the nursing practice. Results showed, to some extent, positive attitude, but the image profile draws attention to nurses' concerns for improving certain system characteristics. The high bar-coding medication administration system skills revealed a more negative perception of the system by the nursing staff. The reasons underlying dissatisfaction with bar-coding medication administration use by skillful users are an important source of knowledge that can be helpful for system development as well as system deployment. As a result, strengthening bar-coding medication administration system usability by magnifying its ability to eliminate medication errors and the contributing factors, maximizing system functionality by ascertaining its power as an extra eye in the medication administration process, and impacting the clinical nursing practice positively by being helpful to nurses, speeding up the medication administration process, and being user-friendly can offer a congenial settings for establishing positive attitude toward system use, which in turn leads to successful bar-coding medication administration system use.
Patients’ Expectations and Perceptions of Service Quality in the Selected Hospitals

Background: Hospital’s success depends on patients’ expectations, perceptions, and judgment on the quality of services provided by hospitals. This study was conducted to assess the patients’ perceptions and expectations from the quality of inpatient health care in Vali-Asr hospital, Ghaemshahr, and Imam Khomeini and Shafa Hospitals, Sari. Materials and Methods: This study is applied regarding the objective of the study. Considering the research methodology, it is a descriptive – analytical study. The sample of this study consists of 600 patients with at least 24 hours of being hospitalized in internal, surgery, women, and children sectors of Vali-Asr, Ghaemshahr, Imam Khomeini, and Shafa Hospitals. Using random sampling method, the classifications relevant to the size of each class were selected. The data required was collected through the standard SERVQUAL questionnaire and then it was analyzed using the SPSS software. Results: The overall mean value and standard deviation of expectations were equal to 10.4 and 28, respectively. The mean value for the field of perception was 69.2 and the relevant standard deviation was 26. In terms of patients and hospital visits in concrete cases, the highest priority is related to empathy. The second priority is related to physical appearance, the third priority is related to responsiveness, the fourth priority is related to assurance, and the lowest priority is related to the reliability of the SERVQUAL approach. Examining the gap between patients’ perceptions and expectations, the widest gap was observed in the Vali-Asr Hospital with the mean and SD (-92.0±39.0) and the lowest gap was observed in Shafa Hospital with the mean value of (-39.9±44.0). According to The Kruskal–Wallis test, the difference observed in these three hospitals were significant. Conclusion: The results showed that patients’ expectations had not been met in any of the examined dimensions and their consent has not been achieved. It seemed that necessary for managers and relevant authorities to plan and pay special attention to this important issue.
Adaptive Control of Semi-Autonomous Teleoperation System With Asymmetric Time-Varying Delays and Input Uncertainties

This paper addresses the adaptive task-space bilateral teleoperation for heterogeneous master and slave robots to guarantee stability and tracking performance, where a novel semi-autonomous teleoperation framework is developed to ensure the safety and enhance the efficiency of the robot in remote site. The basic idea is to stabilize the tracking error in task space while enhancing the efficiency of complex teleoperation by using redundant slave robot with subtask control. To unify the study of the asymmetric time-varying delays, passive/nonpassive exogenous forces, dynamic parameter uncertainties and dead-zone input in the same framework, a novel switching technique-based adaptive control scheme is investigated, where a special switched error filter is developed. By replacing the derivatives of position errors with their filtered outputs in the coordinate torque design, and employing the multiple Lyapunov-Krasovskii functionals method, the complete closed-loop master (slave) system is proven to be state-independent input-to-output stable. It is shown that both the position tracking errors in task space and the adaptive parameter estimation errors remain bounded for any bounded exogenous forces. Moreover, by using the redundancy of the slave robot, the proposed teleoperation framework can autonomously achieve additional subtasks in the remote environment. Finally, the obtained results are demonstrated by the simulation.
Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study

Background and objective: This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study. Methods: The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study. The main study population included 709 cognitively normal subjects at first re-examination who returned to the second re-examination up to 10 years later (incident dementia n = 39). An extended population (n = 1009, incident dementia 151) included non-participants/non-survivors (national registers data). DSI was used to develop a dementia index based on first re-examination assessments. Performance in predicting dementia was assessed as area under the ROC curve (AUC). Results: AUCs for DSI were 0.79 and 0.75 for main and extended populations. Included predictors were cognition, vascular factors, age, subjective memory complaints, and APOE genotype. Conclusion: The supervised machine learning method performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. DSI could thus be useful for identifying individuals who are most at risk and may benefit from dementia prevention interventions.
Properties enhancement and recoil loop characteristics for hot deformed nanocrystalline NdFeB permanent magnets

Nanocrystalline NdFeB magnets were prepared by spark plasma sintering (SPS) and SPS followed by HD using melt spun ribbons as the starting materials. The microstructure of SPSed and HDed magnets were analyzed. The effects of process including temperature and compression ratio on the microstructure and properties were investigated. High magnetic properties were obtained in anisotropic HDed magnets. The combination of Zn and Dy additions was successfully employed to improve the coercivity and thermal stability of the SPSed magnets. Open recoil loops were found in these magnets with Nd-rich composition and without soft magnetic phase for the first time. The relationship between the recoil loops and microstructure for SPS and HD NdFeB magnets were investigated. The investigations showed that the magnetic properties of SPS+HDed magnets are related to the extent of the aggregation of Nd-rich phase, which was formed during HD due to existence of porosity in SPSed precursor. Large local demagnetization fields induced by the Nd-rich phase aggregation leads to the open loops and significantly reduced the coercivity. By reducing the recoil loop openness, the magnetic properties of HDed NdFeB magnets were successfully improved.
Shakedown of Unbound Pavements

ABSTRACT The performance of a pavement material beyond the elastic limit has substantial influence on the bearing capacity of a pavement and its serviceability. But in all the extant design methods for unbound pavements, only the elastic strain or stress at the top of the subgrade of the pavements is used as a design parameter. Although experimental data and practical experience have been introduced into the design method through empirical parameters, there is not a simple relationship between the elastic strain and the long-term plastic behaviour of pavement materials. Furthermore, these methods assume that pavements deteriorate indefinitely, whereas in practice pavements are frequently observed to “shakedown” to a steady state. In this paper, we will review progress in developing a new mechanistic approach to unbound pavement design, based on the shakedown theory, which incorporates the plastic as well as elastic properties of the pavement layers, provides predictions of various failure modes, such as rut formation and subsurface slip, all of which are consequences of unlimited accumulation of plastic deformation. The minimum shakedown loads are found by varying the geometry of the proposed failure mechanisms, and this is done for an unbound pavement overlying a clay subgrade.
Solution to second-order nonhomogeneous generalized Sylvester equations

In this paper, a new type of nonhomogeneous second-order generalized Sylvester equations (GSEs) are proposed. A complete general parametric solution in a neat explicit closed form is established using the F-coprimeness condition. The primary feature of this solution is that the matrix F does not need to be in any canonical form, or may be even unknown a priori. The matrix R, together with the matrix F, may be both set undetermined and used as degrees of freedom beyond the completely free parameter matrix Z. The results provide great convenience to the computation and analysis of the solutions to this class of equations, and can perform important functions in many control systems analysis and design problems involving second-order dynamical systems.
Leader-following rendezvous for single-integrator multi-agent systems with uncertain leader

This paper investigates a nonlinear internal model approach for the leader-following rendezvous problem for a class of single-integrator multi-agent systems subject to an uncertain leader. The problem is first converted into an auxiliary cooperative stabilization with connectivity preservation problem. The latter problem is then solved by a potential function based high-gain feedback control. The theoretical result is also illustrated by a simulation example.