Miracle-dz/UniFAR-FTUs huggingface dataset:
Acoustic Emissions in 3D Printed Parts under Mode I Delamination Test

This paper applies an innovative approach based on the acoustic emission technique to monitor the delamination process of 3D parts. Fused deposition modelling (FDM) is currently one of the most widespread techniques for additive manufacturing of a solid object from a computer model. Fundamentally, this process is based on a layer-by-layer deposition of a fused filament. The FDM technique has evolved to the point where it can now be proposed, not only as a prototyping technique, but also as one applicable to direct manufacturing. Nonetheless, a deeper comprehension of mechanical behavior and its dependence on process parameters must include the determination of material properties as a function of the service load. In this work, the effects of extrusion temperature on inter-layer cohesion are studied using a method employing a double cantilever beam (DCB). The ASTM D5528 standard was used to determine the delamination energy, GI. In addition, the acoustic emission technique was employed to follow the delamination process during testing. Finally, a Charge-Coupled Device (CCD) camera and a calibrated grid was employed to evaluate crack propagation during testing.
Influence of punch geometry (head-flat diameter) and tooling type (‘B’ or ‘D’) on the physical–mechanical properties of formulation tablets

Abstract The presented study assessed the influence of punch geometry (head-flat [HF] diameter) and tooling type (‘B’ or ‘D’) on the physical–mechanical properties of tablets prepared by direct-compression of two guaifenesin (25% or 40% w/w) formulations. Tablets of both formulations were prepared on instrumented, single-layer, rotary tablet press using 10 mm, flat-faced, ‘B’ or ‘D’-type tooling with different HF diameters, and compression forces (CF) ranging from 5 to 25 kN with 5 kN increments. The tablets were evaluated for dimensions, weight variation, tensile strength (TS), friability, and capping index. In general, tablets prepared using ‘D’ tooling showed a significantly (p < 0.05) higher TS compared to those prepared using ‘B’ tooling, likely due to higher dwell-times associated with ‘D’ tooling. Formulations containing 25% w/w guaifenesin showed a significantly (p < 0.05) higher TS compared to those containing 40% w/w guaifenesin, at given compression CF, punch geometry, or tooling type. This could be due to the higher ratio of Prosolv® SMCC contributing to the compressibility. For both formulations compressed using ‘B’ tooling, differences in TS profiles were observed between different HF tooling. The TS of these tablets increased significantly with increasing HF diameter. For formulations compressed using ‘D’ tooling, this trend was observed only up to a CF of 15 kN, beyond which the TS plateaued, possibly due to work-hardening of the formulation at higher CF. These formulations also exhibited capping at CF above 15 kN and with higher HF diameters. The study showed a significant influence of punch geometry and tooling type on the physical properties of tablets.
Separation of Vehicle Detection Area Using Fourier Descriptor Under Internet of Things Monitoring

With the popularity of automobiles, road traffic accidents and congestion have become increasingly serious. Therefore, technologies are needed to solve problems such as speeding and congestion. The detection and tracking of vehicles based on computer vision and Internet of Things monitoring are an important part of the intelligent traffic monitoring system. The angle between the camera and the vehicle will cause the gradually moving vehicles to have a connection during image segmentation. This paper aims to improve the detection accuracy of vehicles from camera images. A new separation method of the vehicle detection area was proposed in this paper. Moving areas are extracted by inter-frame differences, and vehicle areas are formed from the areas. If more than one vehicle area partially overlaps as one area, it is necessary to separate the area. The existing method extracts a place to be separated from an outline of the area. However, it is impossible for the method to separate vehicles using the extracted shape. Therefore, a new method is proposed that makes the place to be separated defined by the reshaping of the area with the use of the Fourier descriptor. The method tries to detect the place from the area. As a result, this method makes it possible to separate the area that the existing method cannot separate and it has obtained a high accuracy of separation in the experimental data of the Internet of Things monitoring.
Human Action Recognition Based on Integrating Body Pose, Part Shape, and Motion

Human action recognition is a challenging problem, especially in the presence of multiple actors in the scene and/or viewpoint variations. In this paper, three modalities, namely, 3-D skeletons, body part images, and motion history image (MHI), are integrated into a hybrid deep learning architecture for human action recognition. The three modalities capture the main aspects of an action: body pose, part shape, and body motion. Although the 3-D skeleton modality captures the actor’s pose, it lacks information about the shape of the body parts as well as the shape of manipulated objects. This is the reason for including both the body-part images and the MHI as additional modalities. The deployed architecture combines convolution neural networks (CNNs), long short-term memory (LSTM), and a fine-tuned pre-trained architecture into a hybrid one. It is called MCLP: multi-modal CNN + LSTM + VGG16 pre-trained on ImageNet. The MCLP consists of three sub-models: CL1D (for CNN1D + LSTM), CL2D (for CNN2D + LSTM), and CMHI (CNN2D for MHI), which simultaneously extract the spatial and temporal patterns in the three modalities. The decisions of these three sub-models are fused by a late multiply fusion module, which proved to yield better accuracy than averaging or maximizing fusion methods. The proposed combined model and its sub-models have been evaluated both individually and collectively on four public data sets: UTkinect Action3D, SBU Interaction, Florence3-D Action, and NTU RGB+D. Our recognition rates outperform the state-of-the-art rates on all the evaluated data sets.
Do Patients Use a Headline Section in a Leaflet to Find Key Information About Their Medicines? Findings From a User-Test Study

Background In the European Union (EU), all medicines are mandated to be provided with a patient information leaflet (PIL). Many patients express concerns about the length and complexity of some PILs, and this can be a disincentive for patients to read the PILS. In order to address this, the UK’s regulatory body (Medicine and Healthcare products Regulatory Agency [MHRA]) suggested leaflets might include a headline section—information presented prominently at the beginning of a leaflet that summarizes key safety messages about a drug. Objective To explore the extent to which readers used a headline section in a PIL, using a form of diagnostic testing called user-testing, which examines how readers find and understand key information. Methods The study used a cross-sectional design to user-test a PIL with a headline section in a target sample of 20 participants. Participants were provided with an exemplar PIL, and the performance of the PIL was evaluated by a questionnaire and semistructured interview. Results The results showed that a headline section was used just over one-third of the time (39%); 90% of participants used the headline section to find information when they initially began the user-test. The qualitative findings suggested that the participants valued the presence of the headline section. Conclusion The research suggests there does not appear to be any negative impact from including a headline section in a PIL, and it is a technique that is highly valued by the consumers of medicines information.
Reduced GLP-1 Secretion at 30 Minutes After a 75-g Oral Glucose Load Is Observed in Gestational Diabetes Mellitus: A Prospective Cohort Study

Glucagon-like peptide 1 (GLP-1) levels may be reduced in type 2 diabetes, but whether a similar impairment exists in gestational diabetes mellitus (GDM) has not been established. We studied this in a prospective cohort study of pregnant women (n = 144) during oral glucose tolerance test (OGTT). GLP-1, glucose, and insulin were sampled at 30-min intervals during a 2-h 75-g OGTT, and indices of insulin secretion and sensitivity were calculated. In a nested case-control study, women with GDM (n = 19) had 12% lower total GLP-1 secretion area under the curve (AUC) compared with control subjects matched for age, ethnicity, and gestational age (n = 19), selected from within the lowest quartile of glucose120 min values in our cohort. GDM had lower GLP-1 response in the first 30 min (19% lower GLP-130 min and 17% lower AUC0–30 min) after adjustment for possible confounders. Their glucose levels began to diverge at 30 min of the OGTT with increasing insulin levels, and by 120 min, their insulin levels were three times higher. In a secondary cohort of 57 women that included “high-normal” glucose120 min values, low GLP-1 AUC0–30 min was independently associated with lower indices of insulin secretion and sensitivity. In conclusion, we have observed that women with GDM have lower GLP-1 response at 30 min of an OGTT and hyperglycemia at 120 min despite significant hyperinsulinemia.
Miniature Planar Spiral Transformer With Hybrid, Ferrite, and Magnetic Nanofluid Core

This paper focuses on a novel, unconventional, hybrid, multi-layered, miniature planar, spiral transformer (MPST) aimed to equip the fly-back convertor for a photovoltaic (PV), energy harvesting (EH) module. The MPST converts the electric parameters (voltage and current) at which the primary “harvestings” stage provides energy to the secondary, conditioning, storage, and delivery stage of the module. The magnetic circuit of the MPST is hybrid, made of ferrite and a specially designed and produced magnetic nanofluid (MNF). Some considerations concerning the preparation and general characterization of the used MNF are included. Then, mathematical models and numerical simulation results that were used in the design phase of the MPST are presented. The electromagnetic field is analyzed for static, stationary, and harmonic working conditions, and the lumped, electric circuit parameters of the MPST are computed. The heat transfer analysis for steady-state conditions shows the good thermal stability of the MPST. Finally, some experiments conducted on the pulsewidth modulation-controlled MPST evidence a very good electric behavior of the dc/dc conversion stage of the PV, EH module.
Review. Classification and Comparison of the Existing SLAM Methods for Groups of Robots

Nowadays the promising line of research is an application of groups of mobile robots to various tasks. An effective SLAM algorithm is one of their main success factors. Due to the increasing popularity of the open-source robots framework, ROS, the best methods should be implemented on this platform. The development should be based on the theoretical research of the subject area. So, the paper is justified by this fact. Multi-robot SLAM methods have been classified according to their key features. Their advantages and disadvantages have been identified. The methods have also been compared according to the available experimental data. The methods most suitable for implementation have been selected.
Opportunistic Resource Scheduling for LTE-Unlicensed With Hybrid Communications Modes

The rapidly increasing amounts of mobile traffic have brought new challenges on the limited spectrum resource. LTE on the unlicensed band, namely, LTE-U, under the carrier aggregation technology has been considered as a potential solution to handle the increasing demand for high data rate that could provide a higher transmission data rate, spectrum efficiency, as well as seamless mobile user experience. To ensure the fairness access between LTE-U BSs in unlicensed bands, in this paper, we consider the multiple LTE-U base stations (BSs) in the same interference region sharing unlicensed bands. We first analyze the hybrid full-duplex/half-duplex transmission mode of LTE-U BSs based on the network status. Although there is throughput gain from the full-duplex transmission, it cannot always provide a superior performance than the half-duplex transmission mode due to the influence of the self-interference. In addition, we further extensively investigate the opportunistic multiple LTE-U BSs access scheme on the unlicensed band based on the channel bidding mechanism to guarantee the opportunistic harmonious sharing on unlicensed bands among LTE-U BSs. Third, a bidding-based dual-band resource allocation scheme is proposed with dynamic hybrid transmission mode to achieve the maximum network utility while guaranteeing the packet delay constraint and minimizing the packet drop rate under the Lyapunov optimization. Finally, various simulation results demonstrate that the algorithm we proposed could achieve a considerable performance improvement with respect to the schemes in the literature.
Expanding Contraceptive Access for Women With Substance Use Disorders: Partnerships Between Public Health Departments and County Jails

Context: Law enforcement has been the primary strategy for addressing the opioid epidemic. As a result, the incarceration rate for women in county jails has increased more than 800% since 1980, and most women inmates struggle with substance use disorders. There is a large unmet need for contraception among women in county jails. Program: The East Region of the Tennessee Department of Health partnered with county correctional facilities to provide comprehensive family planning education and voluntary long-acting reversible contraception (LARC) to women in 15 jails. Implementation: Incarcerated women were invited to attend a comprehensive family planning education session conducted in the jail by health department nurses. The sessions included information on neonatal abstinence syndrome. The nurses explained that the women could receive intrauterine devices, implants, and injectable progesterone while incarcerated and come to the health department for all contraceptive methods upon release. Between January 2014 and June 2017, nurses conducted 182 education sessions, and 794 women received a LARC. Method placement occurred in the jails or at the local health department. No adverse effects were known to have occurred. Evaluation: We collected pilot data to explore the accuracy and the comprehensiveness of the family planning education session and whether the incarcerated women experienced the program as voluntary. All 18 women inmates interviewed reported experiencing the program as voluntary. Using published and administrative data, we roughly estimated that the program prevented between 270 and 460 unintended pregnancies and between 40 and 52 cases of neonatal abstinence syndrome in the first year after the women received a method. This represents a cost savings to Medicaid of $1.4 million. Discussion: The partnership demonstrated the feasibility of providing voluntary comprehensive family planning education and access to highly effective contraception for women inmates who, as a group, face a host of political, socioeconomic, and personal barriers to reproductive health care.
Interaction Design Evaluation and Improvements of Cozora - A Synchronous and Asynchronous Online Learning Aplication

The development of online learning applications has helped student and teacher passed the barriers of space and even time. On online learning, there are two types of learning based on communication method. They are synchronous and asynchronous learning. Cozora is one of online learning applications that provides both synchronous and asynchronous learning in Indonesia. This application helped student to learn directly to the lectures by using live cast. Cozora has been used by APTIKOM-AMIKOM Distance Education Program (APTIKOM-AMIKOM DE Program) to facilitate learning between student (computer science master program) and lectures. Usability and interaction design is one of important aspect in designing online learning applications. Therefore, this study aims to evaluate the interaction design and usability aspect of the system. Evaluation done using online questionnaire, usability testing, and contextual interview. The study found that Cozora has implemented interaction design on its applications. However, there are still some minor improvements that can be done to improve Cozora.
[Computer-assisted decision-making in cardiac surgery: from 3D preoperative planning to computational fluid dynamics in the design of surgical procedures].

INTRODUCTION Although surgical specialties utilize static models for preoperative planning, the evolution of dynamic planning methods and computer simulations created the opportunity for the introduction of dynamic parameters in cardiac surgery. Our aim was to apply 3D models in cardiac surgical practice, predicting fluid dynamic results, ventricular shape, volume and function before the operation. METHODS Using a script developed by us, the raw DICOM files were imported, the dilated left ventricle was modeled and fluid dynamic parameters were simulated, such as flow kinematic and profile analysis, turbulence calculation and myocardial response to shear stress. Then step-by-step simulation of the surgical ventricle restoration procedure was accomplished and the calculated variables were imbedded in silico model. The length of resection lines was modified based on the previous computer simulation and applied during the operation, if feasible. RESULTS The sphericity and conicity indexes were improved significantly in postoperative period (0.42 vs. 0.67 and 0.36 vs. 0.72, p < 0.05). The occurred shear stress at endocardium decreased 83% due to the normalization of flow kinematic pattern of the ventricle in postoperative period (132.21 ± 29.5 dyne/cm2 vs. 22.92 ± 10.3 p < 0.05 dyne/‌cm2). The postoperative turbulent flow pattern significantly decreased, according to our computational method (2712 vs. 1823, p < 0.0001). CONCLUSION With our method, the standardization of the surgical ventricle reconstruction was achievable and the surgical steps were predictable. Therefore, a new decision making support system was established in cardiac surgery for high risk patients. A personalized surgical technique was offered to our patients, improving their life expectancy and quality of life.
Local and global strategies for InSAR phase unwrapping

In the last years, both local and global analysis techniques for the effective processing of interferometric SAR data have been proposed. We developed two local approaches to eliminate inconsistencies in the measured (wrapped) phase field, based on the local configurations of phase gradients in finite windows. The first technique adopts a fixed search strategy which 'cures' isolated residue couples by an appropriate series of corrections determined a priori. A second strategy uses the generalization capabilities of a neural network, trained on a suitable number of simulated target phase fields, to add 2 - (pi) cycles to the proper locations of the interferogram. These approaches, in spite of the high dimensionality of this problem, are able to correctly remove more than half the original number of pointlike inconsistencies on real noisy interferograms. This stems from the observation that phase unwrapping is an ill-posed problem, which has to be solved globally. Hence, a global stochastic method has been implemented, based on the minimization of a functional measuring the regularity of the phase field. The optimization tool used is simulated annealing with constraints. This methodology gives excellent results also in difficult conditions. We will present some of the recent results which aim at integrating the above-mentioned methodologies into powerful processing chains optimized for operating on large IFSAR datasets from real scenes. The effectiveness of such phase retrieving methods allows the application of sophisticated and innovative remote sensing techniques, such as differential interferometry.
Skin Alterations in Pseudoxanthoma Elasticum Patients Highlighted by the Bi-Dimensional Sample Entropy Algorithm

BACKGROUND: Pseudoxanthoma elasticum (PXE) is a hereditary disease that manifests - among others - with papular lesions on the skin. The presence of these papules is the earliest sign of the pathology. Their detection is therefore of importance but, due to their small size, this can become a difficult task. This is why dermoscopy, a noninvasive imaging modality, may be of interest. Nevertheless, the detection of papules on dermoscopic images is still a challenge. OBJECTIVE: We propose an image processing framework to help in the detection of papules from dermoscopic images. Our algorithm is based on the recently-proposed bi-dimensional sample entropy. METHODS: Seven PXE patients participated to the study. For each of them, one dermoscopic image of the neck (where the papules are predominant), and one dermoscopic image of a normal skin zone have been recorded. For each one, the bi-dimensional sample entropy has been computed. RESULTS: We observed statistically significantly lower bi-dimensional sample entropy values on the dermoscopic images of the neck than on the dermoscopic images of the normal zone. CONCLUSION: These preliminary findings show that the bi-dimensional sample entropy might be of interest for the diagnosis and follow-up of the PXE pathology.
Segmentation of Mandibles in Computer Tomography Volumes of Patients with Foam Cells Carcinoma

Computer Tomography (CT) is one of the most used imaging techniques for the proper visualization of body structures with an appropriate resolution for diagnosis and medical procedures. Regarding cancer treatment, CT images are used to guide radiotherapy offering an effective treatment while reducing radiation exposure. In this paper, an automatic mandible segmentation algorithm is proposed. 25 CT volumes were obtained from 2015 MICCAI challenge: Head and neck Auto Segmentation Challenge database. At first, preprocessing is performed by an image size homogenization, followed by a histogram specification and grayscale morphology operations. After that, a vector quantization is done to obtain a proper static threshold for image binarization. Finally, a 3D template matching using cross-correlation was performed to find a point inside the mandible followed by a geodesic dilation using the binary image as mask. For this structure, a mean Dice index of 0.80486 was obtained for the optional test dataset of the challenge.
Sparse Bayesian Learning-Based Space-Time Adaptive Processing With Off-Grid Self-Calibration for Airborne Radar

Space–time adaptive processing (STAP) for airborne radar has recently been enriched owing to the development of methods based on sparse recovery techniques. These methods have shown advantages over the conventional ones. However, there are still difficulties in practical situations, for example, when many clutter components are not located on the discretized sampling grids of the dictionary, which will result in significant performance loss. To deal with such off-grid problem, this paper proposes a sparse Bayesian learning-based STAP (SBL-STAP) with an off-grid self-calibration method, which can effectively mitigate the off-grid effect. In the proposed method, the clutter plus noise covariance matrix is estimated via SBL. Meanwhile, we construct a small-scale complementary dictionary with an adaptive approach to calibrate the uniformly discretized dictionary. In each iteration of the SBL, the atoms of the complementary dictionary renew themselves by an approach based on weighted least squares. In this way, the atoms of complementary dictionary can converge to the clutter ridge adaptively when off-grid occurs. The simulation results show that the clutter ridge spreading caused by off-grid can be mitigated effectively, and the output signal-to-clutter-plus-noise ratio of the STAP is significantly improved. The benefits come at the cost of negligible increase of computational complexity.