Miracle-dz/UniFAR-FTUs huggingface dataset:
Symmetric Nature of Stress Distribution in the Elastic-Plastic Range of Pinus L. Pine Wood Samples Determined Experimentally and Using the Finite Element Method (FEM)

This article presents the results of experimental research on the mechanical properties of pine wood (Pinus L. Sp. Pl. 1000. 1753). In the course of the research process, stress-strain curves were determined for cases of tensile, compression and shear of standardized shapes samples. The collected data set was used to determine several material constants such as: modulus of elasticity, shear modulus or yield point. The aim of the research was to determine the material properties necessary to develop the model used in the finite element analysis (FEM), which demonstrates the symmetrical nature of the stress distribution in the sample. This model will be used to analyze the process of grinding wood base materials in terms of the peak cutting force estimation and the tool geometry influence determination. The main purpose of the developed model will be to determine the maximum stress value necessary to estimate the destructive force for the tested wood sample. The tests were carried out for timber of around 8.74% and 19.9% moisture content (MC). Significant differences were found between the mechanical properties of wood depending on moisture content and the direction of the applied force depending on the arrangement of wood fibers. Unlike other studies in the literature, this one relates to all three stress states (tensile, compression and shear) in all significant directions (anatomical). To verify the usability of the determined mechanical parameters of wood, all three strength tests (tensile, compression and shear) were mapped in the FEM analysis. The accuracy of the model in determining the maximum destructive force of the material is equal to the average 8% (for tensile testing 14%, compression 2.5%, shear 6.5%), while the average coverage of the FEM characteristic with the results of the strength test in the field of elastic-plastic deformations with the adopted ±15% error overlap on average by about 77%. The analyses were performed in the ABAQUS/Standard 2020 program in the field of elastic-plastic deformations. Research with the use of numerical models after extension with a damage model will enable the design of energy-saving and durable grinding machines.
Assessment of early exaggerated treatment effects in orthodontic interventions using cumulative meta-analysis

Summary Background The reported initial strong treatment effects reported in early trials that are refuted in subsequent future studies assessing the same interventions have been attributed to novelty bias. The aim of this study was to determine whether there is any evidence of novelty bias in the reported treatment effects of orthodontics interventions. Materials and methods Relevant orthodontic systematic review (SRs) topics containing at least one meta-analysis on either binary or continuous outcomes with a minimum of three trials considered important areas in the field of orthodontic practice were identified. SR, meta-analysis, and primary study-level characteristics were extracted. Descriptive statistics were calculated at the SRs, meta-analysis, and at the individual study level. All SR and trial-level data were imported into the statistical software and all meta-analyses were replicated using the cumulative random-effects meta-analysis approach. Changes in the size and direction of the estimates between the first trial and the cumulative effect over time were recorded. Results Forty-seven meta-analyses were included. The total number of primary studies included within these meta-analyses was 408 (N = 408). Overall, the final effect size estimate decreased in 29 (61.7%, N = 29/47) cumulative meta-analyses whilst it increased in the remaining 18 (38.3%, N = 18/47). No association between the level of risk of bias and the cumulative absolute effect size was evident (OR 1.00; 95% CI: 0.98, 1.03; P = 0.717) after adjusting for year of the primary study (P = 0.22). Conclusions Clinicians should be wary of the results of trials reporting the effectiveness of new interventions as there is a possibility that the reported effect size will be often exaggerated.
EVALUATION OF POST-TENSION STRENGTHENED STEEL GIRDER BRIDGE USING FRP BARS

Many state, county, and local agencies are faced with deteriorating bridge infrastructure composed of a large percentage of relatively short to medium span bridges. In many cases, these older structures are rolled or welded longitudinal steel stringers acting compositely with a reinforced concrete deck. Most of these bridges, although still in service, need some level of strengthening due to increases in legal live loads or loss of capacity due to deterioration. Although these bridges are overstressed in most instances, they do not warrant replacement; thus, structurally efficient but cost-effective means of strengthening needs to be employed. In the past, the use of bolted steel cover plates or angles was a common retrofit option for strengthening such bridges. However, the time and labor involved to attach such a strengthening system can sometimes be prohibitive. This project was funded through the Federal Highway Administration's Innovative Bridge Research and Construction program. The goal is to retrofit an existing structurally deficient, three-span continuous steel stringer bridge using an innovative technique that involves the application of post-tensioning forces; the post-tensioning forces were applied using fiber reinforced polymer post-tensioning bars. When compared to other strengthening methods, the use of carbon fiber reinforced polymer composite materials is very appealing in that they are highly resistant to corrosion, have a low weight, and have a high tensile strength. Before the post-tensioning system was installed, a diagnostic load test was conducted on the subject bridge to establish a baseline behavior of the unstrengthened bridge. During the process of installing the post-tensioning hardware and stressing the system, both the bridge and the post-tensioning system were monitored. The installation of the hardware was followed by a follow-up diagnostic load test to assess the effectiveness of the post-tensioning strengthening system. Additional load tests were performed over a period of two years to identify any changes in the strengthening system with time. Laboratory testing of several typical carbon fiber reinforced polymer bar specimens was also conducted to more thoroughly understand their behavior. This report documents the design, installation, and field testing of the strengthening system and bridge.
Game Theoretic Analysis of Distributed Systems: Design and Incentives

This dissertation studies incentive aspects of distributed systems in which limited private or public resources must be allocated among selfish autonomic participants. Our goal is to design mechanisms which ensure the efficiency and fairness of resource allocation in such systems. We employ selfish user models and we investigate the results of our proposed schemes. We also design distributed optimization algorithms intended for practical implementation. First, we target backup services in peer-to-peer systems, i.e., distributed networks of functionally equal peers, where users save their backup data on the underutilized storage devices of one another over the Internet. As a main characteristic, no scalability problems arise since more users provide larger overall storage space and bandwidth. Furthermore, spatial and ownership diversity of storage hosts assure the availability of backed up data. However, the management of users not willing to share their local resources with other participants is extremely important to keep the system operational. Moreover, ensuring high quality of service in such a peer-to-peer network requires careful system design. Our novel data redundancy and peer selection policies provide reliable backup service in return for fair resource contribution of the users. Second, we examine the potential of a dynamic spectrum management framework that enables sequential allocation of frequency bands for wireless service providers. We present our distributed system design on allocation and pricing with the goal of achieving efficient spectrum utilization, flexible allocations and incentive-compatibility, considering physical interference among frequency licensees. Our work provides insights on emerging optimization problems related to the allocation. We suggest heuristic solutions to these problems based on our analytic results. We evaluate the proposed framework and algorithms numerically, and we conclude that our proposed heuristics can be the cornerstones of a flexible distributed dynamic allocation system.
Improving Learning Efficiency for Wireless Resource Allocation with Symmetric Prior

Improving learning efficiency is paramount for learning resource allocation with deep neural networks (DNNs) in wireless communications over highly dynamic environments. Incorporating domain knowledge into learning is a promising approach to dealing with this issue. It is also an emerging topic in the wireless community. In this article, we briefly summarize two approaches for using domain knowledge: introducing a mathematical model and prior knowledge to deep learning. Then, we consider a type of symmetric prior permutation equivariance, which widely exists in wireless tasks. To explain how such a generic prior is harnessed to improve learning efficiency, we resort to ranking, which jointly sorts the input and output of a DNN. We use power allocation among subcarriers, probabilistic content caching, and interference coordination to illustrate the improvement of learning efficiency by exploiting the property. From the case study, we find that the required training samples to achieve given system performance decreases with the number of subcarriers or contents, owing to an interesting phenomenon called “sample hardening. ” Simulation results show that the training samples, the free parameters in DNNs, and the training time can be reduced dramatically by harnessing the prior knowledge. The samples required to train a DNN after ranking can be reduced by 15 ∼ 2,400 folds to achieve the same system performance as the counterpart without using prior.
Prevalence and Impact of Diagnosed and Undiagnosed Depression in the United States

Background: The objectives of this study were: 1) estimate the impact and severity of both diagnosed and undiagnosed depression in the general US population 2) explore the demographics of depression based on its common symptoms 3) interpret Patient Health Questionnaire-9 (PHQ-9) scores to improve accuracy in identifying individuals with depression. Methods: A random sample of 200 individuals was selected from a general US adult population to complete the Patient Health Questionnaire-9 (PHQ-9). Results: Only 39.4% of respondents indicated that they had a formal diagnosis of depression. In contrast, 53% of participants have considered seeking help from a mental health professional. More importantly, 31.45% of respondents without a formal diagnosis had a PHQ-9 score of over 10 (moderate to severe depression). Conclusions: The results indicate that undiagnosed depression exists in the US population and suggest that access to mental health services needs to expand across the nation.
Surface Crystallography by LEED: Theory, Computation and Structural Results

1. Introduction. - 1.1 LEED as a Tool for Surface Studies. - 1.2 Purpose of the Computational Programs. - 1.3 Physical Processes Included in the Programs. - 1.4 Capabilities of the Programs. - 1.5 Size, Speed and Limitations of the Programs. - 1.6 Relation to Other LEED Programs. - 1.7 Some Computational Considerations. - 2. The Physics of LEED. - 2.1 A Simple Description of the LEED Process: Clean Crystals and Bragg Reflections in One Dimension. - 2.2 Peak Width and Electron Penetration Depth. - 2.3 Three-Dimensional Effects. - 2.4 Overlayer Effects. - 2.5 Elements of a LEED Theory. - 3. Basic Aspects of the Programs. - 3.1 Units and Geometrical Conventions. - 3.2 Layers, Subplanes and Plane Waves. - 3.3 Superlattices. - 3.4 Atomic Scattering and the Calculation of Phase Shifts. - 3.5 Thermal Vibrations. - 3.6 Ordering of (? ,m) Pairs. - 4. Symmetry and Its Use. - 4.1 Symmetry and Registries. - 4.2 Symmetry Among Beams. - 4.3 Some Formulas. - 4.4 Summary. - 5. Calculation of Diffraction Matrices for Single Bravais-Lattice Layers. - 5.1 Layer Diffraction Matrices. - 5.2 Subroutine MSMF. - 5.3 The Intralayer Multiple-Scattering Matrix X. - 5.4 Scattering Amplitudes and Temperature Effects. - 6. The Combined Space Method for Composite Layers: by Matrix Inversion. - 6.1 The Formalism. - 6.2 Subroutine MTINV. - 7. The Combined Space Method for Composite Layers: by Reverse Scattering Perturbation. - 7.1 The Formalism of Reverse Scattering Perturbation (RSP) Theory. - 7.2 Combining RSP and Matrix Inversion. - 7.3 Subroutine MPERTI. - 8. Stacking Layers by Layer Doubling. - 8.1 The Formalism. - 8.2 Bulk Treatment: Subroutine SUBREF. - 8.3 Surface Treatment: Subroutines ADREF1, DBLG, DBG. - 9. Stacking Layers by Renormalized Forward Scattering (RFS) Perturbation. - 9.1 The Formalism. - 9.2 Subroutines RFS03, RFS02 and Others. - 10. Assembling a Program: the Main Program and the Input. - 10.1 Preparing a Calculation. - 10.2 The Main Program. - 10.3 Explanation of Output. - 10.3.1 Print Output. - 10.3.2 Punch Output. - 10.4 Main Program for Clean fcc (111) and hcp (0001) Faces, Including Possible Top-Layer Registry Shifts, Using RFS. - 10.5 Main Program for a Small-Atom p(2x1) Overlayer on a fcc (111) Substrate, Using RSP and RFS. - 10.6 Main Program for a Clean fcc or bcc (100) Surface, Using RFS. - 10.7 Main Program for a p(2x2) Overlayer on an fcc or bcc (100) Substrate, Using Layer Doubling. - 10.8 Main Program for a c(2x2) Overlayer on an fcc or bcc (100) Substrate, with Rumpling of the Topmost Substrate Layer, Using Matrix Inversion and RFS. - 10.9 Main Program for an Upright Diatomic Molecule on an fcc or bcc (100) Substrate, Using Layer Doubling. - 11. Subroutine Listings. - 12. Structural Results of LEED Crystallography. - 12.1 Non-Metals. - 12.2 Clean Metals. - 12.3 Adsorption on Metals. - 12.4 Bibliography. - Appendix A. Symmetry Among Plane Waves. - Appendix B. Lattice Sums Over Sublattices. - Appendix C. A Line-Printer Plotting Program. - References.
Breeding Wheat for Powdery Mildew Resistance: Genetic Resources and Methodologies—A Review

Powdery mildew (PM) of wheat caused by Blumeria graminis f. sp. tritici is among the most important wheat diseases, causing significant yield and quality losses in many countries worldwide. Considerable progress has been made in resistance breeding to mitigate powdery mildew. Genetic host resistance employs either race-specific (qualitative) resistance, race-non-specific (quantitative), or a combination of both. Over recent decades, efforts to identify host resistance traits to powdery mildew have led to the discovery of over 240 genes and quantitative trait loci (QTLs) across all 21 wheat chromosomes. Sources of PM resistance in wheat include landraces, synthetic, cultivated, and wild species. The resistance identified in various genetic resources is transferred to the elite genetic background of a well-adapted cultivar with minimum linkage drag using advanced breeding and selection approaches. In this effort, wheat landraces have emerged as an important source of allelic and genetic diversity, which is highly valuable for developing new PM-resistant cultivars. However, most landraces have not been characterized for PM resistance, limiting their use in breeding programs. PM resistance is a polygenic trait; therefore, the degree of such resistance is mostly influenced by environmental conditions. Another challenge in breeding for PM resistance has been the lack of consistent disease pressure in multi-environment trials, which compromises phenotypic selection efficiency. It is therefore imperative to complement conventional breeding technologies with molecular breeding to improve selection efficiency. High-throughput genotyping techniques, based on chip array or sequencing, have increased the capacity to identify the genetic basis of PM resistance. However, developing PM-resistant cultivars is still challenging, and there is a need to harness the potential of new approaches to accelerate breeding progress. The main objective of this review is to describe the status of breeding for powdery mildew resistance, as well as the latest discoveries that offer novel ways to achieve durable PM resistance. Major topics discussed in the review include the genetic basis of PM resistance in wheat, available genetic resources for race-specific and adult-plant resistance to PM, important gene banks, and conventional and complimentary molecular breeding approaches, with an emphasis on marker-assisted selection (MAS).
Cancer prognosis with machine learning-based modified meta-heuristics and weighted gradient boosting algorithm

ABSTRACT Cancer is typically a disease that is instigated when cells partition uncontrollably, thereby spread to surrounding tissues. Among different kinds of cancer, breast cancer, cervical and lung cancer have found to experience less screening rate. Hence, detecting such kinds of cancer has become crucial to save individual’s life. With the ability of ML (Machine Learning) for solving complicated tasks in dynamic configurations have contributed to its application in prognosticating cancer with diverse meta-heuristic algorithms. Though conventional researches have attempted to perform this, feature selection process has been inefficient that negatively impacted the accuracy rate. To resolve such consequences, the study considers Wisconsin breast cancer dataset, lung cancer dataset and cervical cancer dataset from UCI ML repository and proposes Modified QPSO-LDA (Quantum Particle Swarm Optimization-Linear Discriminant Analysis) to select suitable and relevant features. Following this, WGB (Weighted Gradient Boosting) is proposed for classification that works based on weighted column subsampling. To validate the performance of this system in prognosticating breast cancer, cervical cancer and lung cancer, analysis is undertaken that confirm its effectiveness with 0.9912 as accuracy for breast cancer dataset, 0.99 as accuracy for cervical cancer dataset and 0.97 as accuracy for lung cancer dataset.
High aerobic fitness in late adolescence is associated with a reduced risk of myocardial infarction later in life : a nationwide cohort study in men

CLINICAL RESEARCH Prevention and epidemiology
WESTERLY WIND EVENTS IN THE TROPICAL PACIFIC, 1986-1995: AN ATLAS FROM THE ECMWF OPERATIONAL SURFACE WIND FIELDS

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The relationship between condition and traffic accidents of urban road intersections in the cold region

More than one thousand traffic accidents scene sketch of Harbin intersections in the cold region in recent five years are analyzed and studied. Through analyzing accidents scene sketch, combining accidents scene with road traffic condition, the relationship between intersection condition and traffic accidents of urban road in the cold region is established, and urban road intersection safety assessing method is presented. According to the circumstances of road, traffic condition and traffic accidents, using synthetic influencing coefficient method, synthetic influencing coefficient "λ" is set up. After initial validating, it is proved that this method is credible and has the function reflecting level of intersection traffic safety, and also can predict the accidents value of some intersections. The results have objective meaning on rational assessing and optimizing designing of urban road intersection.
An Internet Heartbeat

Obtaining sound inferences over remote networks via active or passive measurements is difficult. Active measurement campaigns face challenges of load, coverage, and visibility. Passive measurements require a privileged vantage point. Even networks under our own control too often remain poorly understood and hard to diagnose. As a step toward the democratization of Internet measurement, we consider the inferential power possible were the network to include a constant and predictable stream of dedicated lightweight measurement traffic. We posit an Internet "heartbeat," which nodes periodically send to random destinations, and show how aggregating heartbeats facilitates introspection into parts of the network that are today generally obtuse. We explore the design space of an Internet heartbeat, potential use cases, incentives, and paths to deployment.
Implementing inhibition of return; embodied visual memory for robotic systems

Based on the biological phenomenon of inhibition of return, we introduce an architecture developed for an active robotic vision system where continually updated global information is used to modulate the action selection process for saccadic camera movements. This facilitates, in an extremely efﬁcient way, the fundamental process of avoiding re-saccading to objects previously visited and, thus, is considered to have a wide-ranging application within active vision systems. Inhibition of return (IOR) refers to the suppression of stimuli (objects and events) processing where those stimuli have previously (and recently) been the focus of spatial attention (Lupianez et al., 2006). In this sense, it forms the basis of attentional (and thus visual) bias towards novel objects. Although the neural mechanism underpinning IOR is not completely understood, it is well established that the dorsal frontoparietal network, including frontal eye ﬁelds (FEF) and superior parietal cortex are the primary structures mediating its control (Mayer et al., 2004). These are some of the many modulatory and affecting structures of the deep superior colliculus (optic tectum in non-mammals), the primary motor structure controlling saccade. Although visual information from the retina starts at the superﬁcial superior colliculus, and there are direct connections be-tween the superﬁcial and deep layers, the former cannot elicit saccade directly (Stein and Meredith, 1991). This information has to be subsequently processed by a number of cortical and sub-cortical structures that place it: 1) in context of attentional bias within egocentric saliency maps (posterior parietal cortex) (Gottlieb, 2007), 2) the aforementioned IOR inputs from other modalities (Stein et al., 2002), 3) overriding voluntary saccades (frontal eye ﬁelds) (Stein