Miracle-dz/UniFAR-FTUs huggingface dataset:
Repair Bond Strength of Conventionally and Digitally Fabricated Denture Base Resins to Auto-Polymerized Acrylic Resin: Surface Treatment Effects In Vitro

Denture base fracture is one of the most annoying problems for both prosthodontists and patients. Denture repair is considered to be an appropriate solution rather than fabricating a new denture. Digital denture fabrication is widely spreading nowadays. However, the repair strength of CAD-CAM milled and 3D-printed resins is lacking. This study aimed to evaluate the effect of surface treatment on the shear bond strength (SBS) of conventionally and digitally fabricated denture base resins. One l heat-polymerized (Major base20), two milled (IvoCad, AvaDent), and three 3D-printed (ASIGA, NextDent, FormLabs) denture base resins were used to fabricate 10 × 10 × 3.3 acrylic specimens (N = 180, 30/resin, n = 10). Specimens were divided into three groups according to surface treatment; no treatment (control), monomer application (MMA), or sandblasting (SB) surface treatments were performed. Repair resin was bonded to the resin surface followed by thermocycling (5000 cycles). SBS was tested using a universal testing machine where a load was applied at the resin interface (0.5 mm/min). Data were collected and analyzed using ANOVA and a post hoc Tukey test (α = 0.05). SEM was used for failure type and topography of fractured surfaces analysis. The heat-polymerized and CAD-CAM milled groups showed close SBS values without significance (p > 0.05), while the 3D-printed resin groups showed a significant decrease in SBS (p < 0.0001). SBS increased significantly with monomer application (p < 0.0001) except for the ASIGA and NextDent groups, which showed no significant difference compared to the control groups (p > 0.05). All materials with SB surface treatment showed a significant increase in SBS when compared with the controls and MMA application (p < 0.0001). Adhesive failure type was observed in the control groups, which dramatically changed to cohesive or mixed in groups with surface treatment. The SBS of 3D-printed resin was decreased when compared with the conventional and CAD-CAM milled resin. Regardless of the material type, SB and MMA applications increased the SBS of the repaired resin and SB showed high performance.
CRISPR/Cas9 Mutant Rice Ospmei12 Involved in Growth, Cell Wall Development, and Response to Phytohormone and Heavy Metal Stress

Pectin is one of the constituents of the cell wall, distributed in the primary cell wall and middle lamella, affecting the rheological properties and the cell wall stickiness. Pectin methylesterase (PME) and pectin methylesterase inhibitor (PMEI) are the most important factors for modifying methyl esterification. In this study, 45 PMEI genes from rice (Oryza sativa L.) were screened by bioinformatics tools, and their structure, motifs, cis-acting elements in the promoter region, chromosomal distribution, gene duplication, and phylogenetic relationship were analyzed. Furthermore, CRISPR/Cas9 was used to edit the OsPMEI12 (LOC_Os03G01020) and two mutant pmei12 lines were obtained to explore the functions of OsPMEI in plant growth and development, and under cadmium (Cd) stress. Compared to wild type (WT) Nipponbare, the second inverted internodes of the mutant plants shortened significantly, resulting in the reduction in plant height at mature stage. The seed setting rate, and fresh and dry weights of the mutants were also decreased in mutant plants. In addition, the pectin methylation of pmei12 lines is decreased as expected, and the pectin content of the cell wall increased at both seedling and maturity stages; however, the cellulose and hemicellulose increased only at seedling stage. Interestingly, the growth of the pmei12 lines was better than the WT in both normal conditions and under two phytohormone (GA3 and NAA) treatments at seedling stage. Under Cd stress, the fresh and dry weights were increased in pmei12 lines. These results indicated that OsPMEI12 was involved in the regulation of methyl esterification during growth, affected cell wall composition and agronomic traits, and might play an important role in responses to phytohormones and stress.
Enhancement of yield strength in zirconium metal through high-pressure induced structural phase transition

We report here a high-pressure phase-transition induced strengthening in ultrapure zirconium metal. The determined yield strength shows more than sixfold abrupt increase at the transition pressure of Pc=6GPa, from σyα≈180MPa in the low-pressure phase of α-Zr to σyω≈1180MPa in the high-pressure phase of ω-Zr. The observed enhancement provides an alternate route for material strengthening and is the most significant among the known strengthening techniques for metals. Our findings support the theoretical simulations of the substantial covalent bonding and “rougher” corrugation of slip planes for dislocations in the ω-phase of zirconium.
Regenerative effects of mouse aortic endothelial cells in a murine model of critical limb ischemia

Critical limb ischemia of the is a serious disease that threatens a significant decrease in working ability and disability of patients. Cell therapy may be useful in correcting the endothelial dysfunction that accompanies this disorder. The aim of study was to evaluate the effectiveness of local transplantation of mouse aortic endothelial cells (MAECs) in a model of critical limb ischemia in mice. Materials and methods. Critical limb ischemia in FVB mice was modeled by femoral artery ligation. The primary culture of endothelial cells was obtained from the murine aortic intima. The endothelial phenotype of cells for the expression of CD31, CD38 and CD309 markers was confirmed by flow cytometry and 1•106 MAECs were transplanted intramuscularly into ischemic limb. Tissue perfusion was assessed by laser Doppler flowmetry as well as descriptive histology was used to analyze changes in ischemic muscle after cell transplantation compared to the control group. Results. After MAECs transplantation in animals with modeled critical limb ischemia, the skin of the foot kept pink color and the corresponding temperature of the healthy limb without signs of necrosis of the distal phalanges in contrast to animals of the control group. According to laser Doppler flowmetry data, a significant difference (p ≤ 0.05) in perfusion of ischemic and sham-operated limbs in animals of the control group remained at the level of Δ = 45.7 ± 13.1 %. In animals after MAECs transplantation, the difference of these indicators between limbs was only Δ = 14.0 ± 8.23 % and was not statistically significant. A histological examination of muscle tissue after MAECs transplantation demonstrated the signs of compensatory processes characterized by hyperplasia and hypertrophy of myocyte’s nuclei and lightening of the nucleoplasm with well-defined nucleoli in some myofibrils. In the cytoplasm of myocytes, intermediate Z-discs were clearly visualized, and the number of myofibrils in muscle fibers increased. Conclusion. In animals with model of critical limb ischemia, the transplantation of aorta-derived endothelial cells recover the perfusion of ischemic limbs and improve the histological indicators of muscle tissue.
Research on World Green Tide Phenomenon and the Green Tide Management at Qingdao Yellow Sea

Large-scale green tides can be severely damaging to coastal environments, landscapes, and aquaculture. Once green tides occur, they usually lead to regular disaster problems. In this paper, we focus on introducing the green tide phenomenon and the disasters it causes. In addition, we review typical green tides that have occurred in various countries around the world and the solutions for addressing the disasters. Finally, we conclude with a summary of the green tide disasters and make constructive suggestions for the green tide management.
JACOBI PROCESSES DRIVEN BY FRACTIONAL BROWNIAN MOTION

In this paper we study a Jacobi equation driven by fractional Brownian motion with Hurst index $H\in (\frac{1}{2},1). $ We first prove the existence and uniqueness of the solution. Then we investigate Malliavin differentiability and smoothness of the density of the solution. Finally, we point out that the solution can be approximated by semimartingales.
Observational test of hot flow anomaly formation by the interaction of a magnetic discontinuity with the bow shock

The formation of a hot flow anomaly (HFA) observed near the Earth`s bow shock appears to be due to the interaction between the bow shock and an impinging discontinuity in the upstream plasma. Recent single-particle and two-dimensional hybrid numerical studies have suggested that such an interaction will produce an HFA only if the motional electric field in the ambient plasma points toward the discontinuity, thereby focusing shock-reflected ions into it. The authors perform a test of this electric field orientation for a set of nine HFA events observed by the ISEE spacecraft and described previously in the literature. The principal difficulty with the test is the determination of the normals to the discontinuities. Application of a minimum variance analysis produces discontinuity normals which suggest that the majority of the discontinuities were probably tangential, even though it is doubtful that the conditions for validity are very well satisfied for these events. Under the assumption that the discontinuities were tangential, the predicted electric field orientations is found on at least one side of all nine observed HFAs (on the trailing edge of seven and the leading edge of five, and on both sides of three events). Further, there is evidence that asymmetriesmore » in the observed magnetic field signatures are related to the orientation of the motional electric field: the events in which the electric field points toward the discontinuity on both sides tend to be those with fairly symmetric flanking magnetic field enhancements. Two-dimensional hybrid simulations appear to confirm the association between the magnetic field signature and the electric field orientations, and they show further that rotational discontinuities appear to be less effective at producing distinct HFA-like signatures than tangential discontinuities. 16 refs., 6 figs., 3 tabs. « less
Invertibility of linear combinations of two idempotents

Let P and Q be two idempotents on a Hilbert space. In this note, we prove that the invertibility of the linear combination λ 1 P + λ 2 Q is independent of the choice of λ i , i = 1, 2, if λ 1 λ 2 ≠ 0 and λ 1 + λ 2 ≠ 0.
Digital Holography Based Three-Dimensional Multi-Target Locating for Automated Cell Micromanipulation

Microrobotic contact manipulation enables automated and precise cell capture, positioning and screening and has potential in biomedical engineering and disease detection. However, when using an optical microscope for visual positioning of targets, the poor clarity, limited cell-background contrast and lack of global 3D information of the cells in the field of view hinder global strategy making and automation, thereby affecting the accuracy and efficiency of manipulation. Here, we propose the 3D locating of multiple biological targets based on digital holography. Global–local combined visual feedback is developed for overall spatial locating and partial locating in a liquid-phase bright-field environment. By applying a filtering-based planar locating algorithm and maximum-area-based depth detection algorithm, the 3D global distribution of micro-targets in the field of view is periodically updated with a high detection rate. By applying a planar locating algorithm based on a convolutional neural network and a depth detection algorithm based on a gradient descent, the 3D fast locating of targets is performed precisely. Experiments show that the detection rate of the global positioning is 95.1%, the mean average precision of the local planar positioning is 90.53%, and the deviation of the local depth positioning is $1.22~\mu \text{m}$ . When capturing cells, this method reaches an average speed of 7.4 cells/min and a collection rate of 90.5%. We anticipate that our method will support the research in cell-based bioengineering including cell screening and early disease diagnosis. Note to Practitioners—Automated cell manipulation is one of the most significant techniques in cell-based biomedical applications. This paper introduces a three-dimensional multi-target visual positioning method for automated cell manipulation. Combining with holographic imaging technique, the global information for the cells in the limited field of view is provided with improved imaging clarity and extended depth of field. The visual recognition algorithm can screen and extract the rare cells in the cell population, which will support the research in the field of early disease diagnosis and biomedicine. The research outcome provides an effective and precise solution to achieve biological targets positioning, capture, and screening within 3D liquid-phase bright-field environment.
User vs. System Conceptual Models of Productivity and Accountability in Human-Machine Interaction

In human-machine interaction (HMI), productivity is based on the performance of the system or user. Similarly, different mental models may exist when assessing accountability for productivity between a human or system. The present research examines how differences between user and system-based mental models of productivity and accountability affect perceived usability, usefulness, and intention to use technology within the Technology Acceptance Model framework. Differential models of productivity and accountability showed differences in the relationship between usefulness, usability, and intention to use an intelligent productivity application. This research demonstrates that differing mental models of productivity and accountability within HMI teams may impact adoption of technology.
Prioritization of bioactive compounds envisaging yohimbine as a multi targeted anticancer agent: insight from molecular docking and molecular dynamics simulation

Abstract Recently, multi-targeted drugs have attracted much attention in cancer therapy where several therapeutic proteins are targeted by a single agent. Using the published scientific literature, we selected sixteen well-known anticancer targets and seven potential phytobioactive chemicals to find a multitargeted compound by screening through molecular docking. The feasible protein–ligand interaction was further predicted by protein–ligand interaction analysis and molecular dynamic simulation. The phytochemical yohimbine exhibited the lowest docking score in the range of −8.3 to −10.0 kcal/mol over other ligands with all the studied protein targets. Molecular interaction data also revealed the feasible binding of yohimbine with all targets. Moreover, the molecular simulation data also confirmed the stability of protein-ligand complexes with three most scored targets viz. ERK2, PARP1 and PIK3α. Based on our results, yohimbine seems to be the most potent compound out of those selected compounds and can be considered as effective lead molecule against the studied target proteins. Communicated by Ramaswamy H. Sarma
Using Formal Methods to Support the Development of STLs for GPUs

Graphics Processing Units (GPUs) boost the development of high-performance safety-critical applications. The reliability of such systems is of utmost importance since faults affecting the hardware may occur at any time during the systems' operational life. Thus, methods to effectively test these devices during their in-field operation are necessary. One popular solution relies on Software Test Libraries (STLs), which recently have been started being used for G PU s as well, since they are effective in terms of fault detection capabilities, intrusiveness, flexibility, and test duration. A drawback of the STL approach for G PU s is the extensive effort used to develop effective test routines for complex structures, e.g., controllers, due to the complicated constraints stemming from the ISA, the available compilation flows and parallelism constraints. We propose a novel technique based on formal methods to support the generation of stimuli and enhance the quality of pre-existing STLs for GPUs. To validate the proposed method, we resort to an open-source GPU model (Flex GripPlu s). Experimental results show that the method can effectively generate complementary code fragments to be added to existing STLs and increase their fault coverage. In the case of the GPU's decoding unit, the stuck-at fault coverage was increased by nearly 10%.
A Foreground Mismatch and Memory Harmonic Distortion Calibration Algorithm for TIADC

This paper proposes a foreground digital calibration algorithm that estimates and corrects the offset, gain, and time-skew mismatches for time-interleaved analog-to-digital converters (TIADCs) furthermore our algorithm is designed to correct for harmonic distortion introduced by the presence of a nonlinear front-end. We propose a novel simplified non-linear model in place of the more complex conventional Volterra series based structure. The mismatch estimation technique based on the Fast Fourier Transform (FFT) is proposed to estimate the various time-interleaving mismatches simultaneously. A Taylor-based technique is applied to compensate for these mismatches. We also consider the choice of an appropriate time reference for the time-skew correction algorithm by theoretical analysis. The nonlinear distortion correction technique is based on estimating and inverting an assumed $3^{\text {rd}}$ order nonlinearity with a fractional delay. To do this, we design a customized filter in an offline process. Our algorithms are designed to operate in any Nyquist zone. The proposed techniques are verified by a Xilinx Zynq UltraScale+ RFSoC ZCU111 evaluation kit containing a 12-bit, 4.096 GHz TI-ADC with 8 sub-ADCs operating in the $2^{\text {nd}}$ Nyquist zone. Accordingly, we observed an improvement in SFDR of 14 dB for mismatch calibration alone and up to another 12 dB with nonlinear correction enabled.
eTagger - An Energy Pattern Tagging Tool for GitHub Issues in Android Projects

Energy efficiency is an essential consideration in mobile application development, given that these apps run on battery-powered devices. This has led the researchers to develop a set of energy design patterns that can help the developers improve the energy efficiency of their applications. However, the adoption of these energy patterns in projects remains a challenge, given the lack of awareness about these patterns among the developers. To bridge this gap, we propose our tool eTagger, a Google Chrome extension that tags GitHub issues from Android repositories with associated energy patterns. eTagger works based on the embeddings generated by Sentence-BERT. We believe that labeling the GitHub issues with energy patterns may help towards their larger adoption as GitHub is a prominent platform in collaborative software development. A preliminary evaluation of eTagger achieved an AUC-ROC of 0.73 with a precision of 0.58, recall of 0.53 and an F1-score of 0.5. The demonstration of the tool is available at https://youtu.be/hP4pWJ4AKxE and related artifacts at https://rishalab.github. io/eTagger/.
Balanced Standing on One Foot of Biped Robot Based on Three-Particle Model Predictive Control

Balancing is a fundamental task in the motion control of bipedal robots. Compared to two-foot balancing, one-foot balancing introduces new challenges, such as a smaller supporting polygon and control difficulty coming from the kinematic coupling between the center of mass (CoM) and the swinging leg. Although nonlinear model predictive control (NMPC) may solve this problem, it is not feasible to implement it on the actual robot because of its large amount of calculation. This paper proposes the three-particle model predictive control (TP-MPC) approach. It combines with the hierarchical whole-body control (WBC) to solve the one-leg balancing problem in real time. The bipedal robot’s torso and two legs are modeled as three separate particles without inertia. The TP-MPC generates feasible swing leg trajectories, followed by the WBC to adjust the robot’s center of mass. Since the three-particle model is linear, the TP-MPC requires less computational cost, which implies real-time execution on an actual robot. The proposed method is verified in simulation. Simulation results show that our method can resist much larger external disturbance than the WBC-only control scheme.
ParRADMeth: Identification of Differentially Methylated Regions on Multicore Clusters

The discovery of Differentially Methylated (DM) regions is an important research field in biology, as it can help to anticipate the risk of suffering from specific diseases. Nevertheless, the high computational cost of the bioinformatic tools developed for this purpose prevents their application to large-scale datasets. Hence, much faster tools are required to further progress in this research field. In this work we present ParRADMeth, a parallel tool that applies beta-binomial regression for the identification of these DM regions. It is based on the state-of-the-art sequential tool RADMeth, which proved superior biological accuracy compared to counterparts in previous experimental evaluations. ParRADMeth provides the same DM regions as RADMeth but at significantly reduced runtime thanks to exploiting the compute capabilities of common multicore CPU clusters. For example, our tool is up to 189 times faster for real data experiments on a cluster with 16 nodes, each one containing two eight-core processors. The source code of ParRADMeth, as well as a reference manual, are available at https://github.com/UDC-GAC/ParRADMeth.
Determination of Poisson’s Ratio by Spherical Indentation Using Neural Networks—Part II: Identification Method

In a previous paper it has been shown that the load and the unloading stiffness are, among others, explicit functions of the Poisson's ratio, if a spherical indenter is pressed into a metal material. These functions can be inverted by using neural networks in order to determine the Poisson's ratio as a function of the load and the unloading stiffness measured at different depths. Also, the inverse function possesses as an argument the ratio of the penetration depth and that depth, at which plastic yield occurs for the first time. The latter quantity cannot he measured easily. In the present paper some neural networks are developed in order to identify the value of Poisson's ratio. After preparing the input data appropriately, two neural networks are trained, the first one being related to Set 2 of the previous paper. In order to avoid an explicit measurement of the yield depth, the second neural network has to be trained in such a way, that its solution intersects with that of Set 2 at the correct value of Poisson's ratio. This allows to identify Poisson's ratio with high accuracy within the domain of finite element data.