Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Associated with Quality of Life in Patients with Type 2 Diabetes of South Benin: A Cross-Sectional Study

Background: Type 2 diabetes (T2D) adversely affects health-related quality of life (QoL). However, little is known about the QoL of diabetic patients in Benin, where the disease is a growing concern. Thus, this study aims to assess the QoL and its associated factors among T2D patients in Cotonou, southern Benin. Methods: A total of 300 T2D patients (age > 18 years) were enrolled, and the diabetes-specific quality of life (DQoL) and Natividad self-care behaviors’ (SCB) instruments were used for data collection. DQoL scores were calculated, and factors associated with DQoL explored using logistic regression. Results: The mean of patients’ DQoL was 38.1 ± 4.1, with 43% having low QoL. In terms of DQoL, 56.3% reported a high diabetes impact, followed by low life satisfaction (53%) and high worry about diabetes (32.7%). In the logistic regression analysis, education, marital status, occupation, family history of diabetes, complications, and social support were associated with DQoL. SCB factors, including healthy eating, problem-solving, coping strategies, and risk reduction, were significant predictors of DQoL. Conclusions: Patients’ empowerment, starting with self-management education, is essential to improve the QoL of T2D patients in Cotonou. However, the programs need to target low education, low socioeconomic status, low social support, and overweight patients.
Exenatide Once Weekly for Management of Type 2 Diabetes: A Review

Abstract Exenatide is one of the exendin-based glucagon-like peptide 1 receptor agonists (GLP-1RAs) and is currently available in two formulations, ie, exenatide twice daily (BID), a short-acting GLP-1RA, and exenatide once weekly (QW), a long-acting GLP-1RA. Clinical efficacy and safety of exenatide 2 mg QW in patients with type 2 diabetes (T2DM) has been demonstrated in the DURATION study program. Exenatide QW has been shown to achieve greater HbA1c reduction compared with exenatide BID, with less injection frequency and greater treatment satisfaction. However, exenatide QW failed to show a significant cardiovascular risk reduction in a cardiovascular outcome trial (CVOT), the EXSCEL trial, while other GLP-1RAs have shown positive CV outcomes. Furthermore, exenatide QW has been shown to be inferior to liraglutide and semaglutide with respect to HbA1c or body weight reduction in the head-to-head trials. Thus, although the long-term efficacy and safety of exenatide QW have been demonstrated, exenatide QW might be selected with lower priority within the class of GLP1-RAs for the management of T2DM, especially for patients at high CV risk. On the other hand, exenatide QW is now expected to be a treatment option for children with T2DM or patients with Parkinson’s disease. This review provides an overview of the current evidence regarding the clinical efficacy and safety of exenatide QW and discusses the current perspectives on exenatide QW for treatment of T2DM.
Open-Rotor low speed aero-acoustics: wind tunnel characterization of an advanced blade design in isolated and installed configurations

This paper presents aeroacoustic data from the HERA rig (HElices RApides), measured during a 2012 wind tunnel test campaign in DNW’s Large Low-speed Facility (LLF). This campaign dealt with two different Snecma blade geometries: a baseline aero-mechanical design, and a subsequent low noise aeroacoustic design, both derived from the DREAM European program (FP7) studies on blade optimization. In order to assess the benefits of the new generation blade design, back to back comparisons of the far field noise of both geometries are carried out, thanks to inflow and out-of-flow acoustic measurements. A variety of blade pitch settings have been tested for the aeroacoustic geometry, for different Mach numbers, rotational speeds and angles of attack. In order to partially reproduce a rear-fuselage pusher engine configuration, an Airbus pylon has been installed upstream of the front rotor. The effects of this pylon representative of an aircraft installation and of its associated trailing edge blowing technology are assessed. The results highlight the pylon blowing efficiency to reduce the pylon-rotor interaction noise. This investigation is carried out with the advanced Snecma blade design and an improved Airbus pylon that takes into account actual aircraft installation constraints.
A Graph Convolution Network-Based Bug Triage System to Learn Heterogeneous Graph Representation of Bug Reports

Many bugs and defects occur during software testing and maintenance. These bugs should be resolved as soon as possible, to improve software quality. However, bug triage aims to solve these bugs by assigning the reported bugs to an appropriate developer or list of developers. It is an arduous task for a human triager to assign an appropriate developer to a bug report, when there are several developers with different skills, and several automated and semi-automated triage systems have been proposed in the last decade. Some recent techniques have suggested possibilities for the development of an effective triage system. However, these techniques require improvement. In previous work, we proposed a heterogeneous graph representation for bug triage, using word–word edges and word-bug document co-occurrences to build a heterogeneous graph of bug data. Cosine similarity is used to weight the word–word edges. Then, a graph convolution network is used to learn a heterogeneous graph representation. This paper extends our previous work by adopting different similarity metrics and correlation metrics for weighting word–word edges. The method was validated using different small and large datasets obtained from large-scale open-source projects. The top-k accuracy metric was used to evaluate the performance of the bug triage system. The experimental results showed that the point-wise mutual information of the proposed model was better than that of other word–word weighting methods, and our method had better accuracy for large datasets than other recent state-of-the-art methods. The proposed method with point-wise mutual information showed 3% to 6% higher top-1 accuracy than state-of-the-art methods for large datasets.
Knee Injury Detection Using Deep Learning on MRI Studies: A Systematic Review

The improved treatment of knee injuries critically relies on having an accurate and cost-effective detection. In recent years, deep-learning-based approaches have monopolized knee injury detection in MRI studies. The aim of this paper is to present the findings of a systematic literature review of knee (anterior cruciate ligament, meniscus, and cartilage) injury detection papers using deep learning. The systematic review was carried out following the PRISMA guidelines on several databases, including PubMed, Cochrane Library, EMBASE, and Google Scholar. Appropriate metrics were chosen to interpret the results. The prediction accuracy of the deep-learning models for the identification of knee injuries ranged from 72.5–100%. Deep learning has the potential to act at par with human-level performance in decision-making tasks related to the MRI-based diagnosis of knee injuries. The limitations of the present deep-learning approaches include data imbalance, model generalizability across different centers, verification bias, lack of related classification studies with more than two classes, and ground-truth subjectivity. There are several possible avenues of further exploration of deep learning for improving MRI-based knee injury diagnosis. Explainability and lightweightness of the deployed deep-learning systems are expected to become crucial enablers for their widespread use in clinical practice.
High Dream Recall Frequency is Associated with Increased Creativity and Default Mode Network Connectivity

Introduction Several results suggest that the frequency of dream recall is positively correlated with personality traits such as creativity and openness to experience. In addition, neuroimaging results have evidenced different neurophysiological profiles in high dream recallers (HR) and low dream recallers (LR) during both sleep and wakefulness, specifically within regions of the default mode network (DMN). These findings are consistent with the emerging view that dreaming and mind wandering pertain to the same family of spontaneous mental processes, subserved by the DMN. Methods To further test this hypothesis, we measured the DMN functional connectivity during resting wakefulness, together with personality and cognitive abilities (including creativity) in 28 HR and 27 LR. Results As expected, HR demonstrated a greater DMN connectivity than LR, higher scores of creativity, and no significant difference in memory abilities. However, there was no significant correlation between creativity scores and DMN connectivity. Discussion These results further demonstrate that there are trait neurophysiological and psychological differences between individuals who frequently recall their dreams and those who do not. They support the forebrain and the DMN hypotheses of dreaming and leave open the possibility that increased activity in the DMN promotes creative-thinking during both wakefulness and sleep. Further work is needed to test whether activity in the DMN is causally associated with creative-thinking.
Creep and Shrinkage Models for High Strength Concrete – Proposals for Inclusion in AS3600

Abstract The Australian Standard for Concrete Structures, AS3600-20011, is currently under review, with the intention to expand its scope to include concrete with characteristic compressive strengths up to 100 MPa. The current procedures in the Standard for the estimation of the strength and deformation characteristics of concrete must be revised, including the tensile strength, the elastic modulus, the creep coefficient and the shrinkage strain. In this paper, the factors that should be considered in such a review are discussed and models for predicting these instantaneous and time-dependent material characteristics are presented. These models are currently under consideration for inclusion in the next edition of the Standard.
Chlorhexidine added to different adhesive systems - Assessment of antibacterial activity and bond strength

This study aimed to assess the effects of adding chlorhexidine (CHX) to different adhesive systems on antibacterial activity and bond strength after 24 hours and 30 days under in vitro conditions. A total of 210 bovine incisor crowns and divided into three groups, based on the adhesive system: Single Bond Plus (SB), Clearfil SE Bond (CL), and AdheSE Primer and Bond (AD). All groups were subdivided by CHX concentration (n=7): no CHX, CHX applied before the adhesive (CPA), and the adhesive incorporated with 0.5% CHX, 1.0% CHX, and 2.0% CHX. The micro shear test was conducted on one-half of the specimens after 24 hours, and on the other half after 30 days. Antibacterial activity was evaluated using the agar diffusion test with Streptococcus mutans. The bond strength variable was assessed using the factorial analysis of variance for repeated measurements, whereas the variable of the bacterial halo size was subjected to the Kruskal–Wallis nonparametric test. The significance level was 5% for both tests. The qualitative variable of fracture pattern was assessed by descriptive statistical analysis. Thus, CHX concentration of 2% (10.80 ±2.83) and CPA (9.95 ±1.47) (p >0.05) helped to increase the bond strength values for most adhesive systems, whereas CL had the highest bond strength values. The CL adhesive system also presented the best results in the antibacterial test with S.mutans.
A Wearable System for Jump Detection in Inline Figure Skating

This article presents the design and experimental evaluation of a non-invasive wearable sensor system that can be used to acquire crucial information about athletes’ performance during inline figure skating training. By combining distance and time-of-flight sensors and gyroscopes, the system is able to detect when jumps are performed and provides a live view of the data (e.g., the number and height of jumps) through a graphical user interface. The main novelty of our approach lies in the way in which the optical sensors are orientated. Typically, the sensors are orientated horizontally and positioned in pairs on the ground, where they measure the time interval between the moment the athlete leaves the ground and the moment they land. In our system, an optical sensor is placed under each foot and is vertically orientated so as to constantly measure the distance from the ground. In addition, a gyroscope sensor is placed on the athlete’s back, which provides information on the direction and angular momentum of the movement. By combining this data, the system provides the accurate detection of various jumps and technical elements without any constraints on the training ground. In this paper, the system is also compared to similar platforms in the literature, although there are no other specific systems that are available for inline figure skating. The results of the experimental evaluation, which was performed by high profile athletes, confirm its effectiveness in correctly detecting jumps, especially considering its compromise between precision and the overall cost of the equipment.
The Contribution of Convection to the Stratospheric Water Vapor: The First Budget Using a Global Storm‐Resolving Model

The deepest convection on Earth injects water in the tropical stratosphere, but its contribution to the global stratospheric water budget remains uncertain. The Global Storm‐Resolving Model ICOsahedral Non‐hydrostatic is used to simulate the moistening of the lower stratosphere for 40 days during boreal summer. The decomposition of the water vapor budget in the tropical lower stratosphere (TLS, 10°S–30°N, and 17–20 km altitude) indicates that the average moistening (+21 Tg) over the simulated 40‐day period is the result of the combined effect of the vertical water vapor transport from the troposphere (+27 Tg), microphysical phase changes and subgrid‐scale transport (+2 Tg), partly compensated by horizontal water vapor export (−8 Tg). The very deep convective systems, explicitly represented thanks to the employed 2.5 km grid spacing of the model, are identified using the very low Outgoing Longwave Radiation of their cold cloud tops. The water vapor budget reveals that the vertical transport, the sublimation and the subgrid‐scale transport at their top contribute together to 11% of the water vapor mass input into the TLS.
Deviation between the sliding direction of the chip over the tool and the direction of the friction force in oblique cutting

Pure oblique cutting experiments with conventional cutting tools as well as ultra-sharp tools have been carried out under a wide range of cutting conditions using a linear slide based cutting set-up. The chip flow direction was measured using the 3D Digital Image Correlation (DIC) technique of high-speed stereoscopic images and the frictional force direction was determined from forces. It is estimated that the error in chip flow angle measurements using DIC, was approximately 1°, as was the error in friction force direction measurements from forces. An increasing trend of the angles with an increase in feed and a decreasing trend of the angles with an increase in speeds were observed. It was found that under many conditions, there is a significant difference between the chip flow direction and the friction force direction. This difference decreases with increase in friction co-efficient and with increasing sharpness of the cutting edge.However, with ultra-sharp microtome knives there is a small but finite difference between the chip flow direction and the friction force direction. By the use of DIC to measure the chip flow angle at different points along the back of the chip, it is found that there was no variation in chip-flow angle over the width of the chip.
Influence of Non-Metallic Inclusions on Local Deformation and Damage Behavior of Modified 16MnCrS5 Steel

This work investigates a ferrite matrix with multiple non-metallic inclusions to evaluate their influence on the global and local deformation and damage behavior of modified 16MnCrS5 steel. For this purpose, appropriate specimens are prepared and polished. The EBSD technique is used to record local phase and orientation data, then analyze and identify the size and type of inclusions present in the material. The EBSD data are then used to run full phase crystal plasticity simulations using DAMASK-calibrated material model parameters. The qualitative and quantitative analysis of these full phase simulations provides a detailed insight into how the distribution of non-metallic inclusions within the ferrite matrix affects the local stress, strain, and damage behavior. In situ tensile tests are carried out on specially prepared miniature dog-bone-shaped notched specimens in ZEISS Gemini 450 scanning electron microscope with a Kammrath and Weiss tensile test stage. By adopting an optimized scheme, tensile tests are carried out, and local images around one large and several small MnS inclusions are taken at incremental strain values. These images are then processed using VEDDAC, a digital image correlation-based microstrain measurement tool. The damage initiation around several inclusions is recorded during the in situ tensile tests, and damage initiation, propagation, and strain localization are analyzed. The experimental results validate the simulation outcomes, providing deeper insight into the experimentally observed trends.
Precise Navigation for an Agricultural Robot

This report is exploring the advantages and disadvantages with some common sensors needed when positioning a mobile robot with Ackerman steering. Both absolute and relative methods are explored. Odometry based on measuring traveled distance and steering angle is tested and adjusted to obtain the best performance. A Kalman filter is constructed to improve steering angle measurements. The tests are based on an agricultural robot tended to follow a row of sugar beets while weeding it. Best position estimate was obtained with the Kalman filter filtering the steering angle information from the steering motor and the information from the difference in velocity on the rear wheels. The average error in this measurement was 6.84%/m.
Roughness-Induced Pavement–Vehicle Interactions

Pavement roughness affects rolling resistance and thus vehicle fuel consumption. When a vehicle travels at constant speed on an uneven road surface, the mechanical work dissipated in the vehicle's suspension system is compensated by vehicle engine power and results in excess fuel consumption. This dissipation depends on both road roughness and vehicle dynamic characteristics. This paper proposes, calibrates, and implements a mechanistic model for roughness-induced dissipation. The distinguishing feature of the model is its combination of a thermodynamic quantity (energy dissipation) with results from random vibration theory to identify the governing parameters that drive the excess fuel consumption caused by pavement roughness, namely, the international roughness index (IRI) and the waviness number, w (a power spectral density parameter). It is shown through sensitivity analysis that the sensitivity of model output, that is, excess fuel consumption, to the waviness number is significant and comparable to that of IRI. Thus, introducing the waviness number as a second roughness index, in addition to IRI, allows a more accurate quantification of the impact of surface characteristics on vehicle fuel consumption and the corresponding greenhouse gas emissions. This aspect is illustrated by application of the roughness–fuel consumption model to two road profiles extracted from FHWA's Long-Term Pavement Performance database.
Molecular DNA Sensors to Measure Distribution of Cytoskeletal Forces

Actin, a major cytoskeletal biopolymer in eukaryotic cells, is crosslinked into networks of filaments and bundles. These networks are largely responsible for the maintenance of cellular shape, rigidity, and mechanical stability. Other assemblies of actin are involved in a myriad of cellular processes, such as cell migration, division, intracellular transport, and morphogenesis. In these processes, the spatial and temporal regulation of the network structure, their dynamics, and force generation due to myosin motors are crucial. Experimentally, one of the challenges is to measure force transmission across such networks, which is vital to properly understand the function, failure, and repair mechanisms beyond the linear regime. To measure forces across the cytoskeletal network, we have developed a FRET-based, reversible DNA force sensor. We employ these DNA constructs as flexible crosslinkers across semiflexible actin, thereby reconstituting model networks of cytoskeletal structures. Characterization of the rheology and frequency response of these model actin-DNA sensor networks is performed via a macrorheometer and also by utilizing a large bandwidth, high-resolution microrheology set up. DNA force sensors are crosslinked in vitro with actin filaments in order to map force distributions and stress relaxations in the resulting network. We characterize the DNA force sensor in solution and across actin networks through fluorescence lifetime imaging microscopy (FLIM) measurements. From these results, we estimate the FRET efficiency of our DNA sensor. We also test DNA sensors in a cellular environment and describe its preliminary results.
Fabrication of High Surface Area Microporous ZnO from ZnO/Carbon Sacrificial Composite Monolith Template

Fabrication of porous materials from the standard sacrificial template method allows metal oxide nanostructures to be produced and have several applications in energy, filtration and constructing sensing devices. However, the low surface area of these nanostructures is a significant drawback for most applications. Here, we report the synthesis of ZnO/carbon composite monoliths in which carbon is used as a sacrificial template to produce zinc oxide (ZnO) porous nanostructures with a high specific surface area. The synthesized porous oxides of ZnO with a specific surface area of 78 m2/g are at least one order of magnitude higher than that of the ZnO nanotubes reported in the literature. The crucial point to achieving this remarkable result was the usage of a novel ZnO/carbon template where the carbon template was removed by simple heating in the air. As a high surface area porous nanostructured ZnO, these synthesized materials can be useful in various applications including catalysis, photocatalysis, separation, sensing, solar energy harvest and Zn-ion battery and as supercapacitors for energy storage.