Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of damage growth by measuring the chord modulus , microhardness and macrohardness variation in ST 37 steel

In this paper, using the theory of Continuum Damage Mechanic and experimental met hods, damage evolution is investigated. There are various experimental and theorical methods for measuring the Damage in materials. the experimental methods can be categorized in two type, i) destructive methods like analysis of chord modulus variation, and the ii) non-destructive methods like microhardness or macrohardness evaluation. In this paper at the first, true stress true strain diagram of material using the simple tension test and chord modulus variation using repetitive loading unloading test is obtained. For measuring plastic strain, grids are etched on the tension sample by using electroetch device. And then by measuring major ellipsoid diameter on the broken sample and comparing with the preceding circle, plastic strain at different points is specified. At specified points of the sample, the microhardness and the macrohardness are measured. Using the data of these three experimental methods, the corresponding damage of is evalvated and the corresponding charts are ploted. finally The evaluated damage by these three methods is compared. It’s observed microhardness and L-U-T test have relatively similar progress, but macrohardness progress had a significant difference with these two methods. It’s also observed, average of three methods is close to microhardness method rather than two other.
SuMa++: Efficient LiDAR-based Semantic SLAM

Reliable and accurate localization and mapping are key components of most autonomous systems. Besides geometric information about the mapped environment, the semantics plays an important role to enable intelligent navigation behaviors. In most realistic environments, this task is particularly complicated due to dynamics caused by moving objects, which can corrupt the mapping step or derail localization. In this paper, we propose an extension of a recently published surfel-based mapping approach exploiting three-dimensional laser range scans by integrating semantic information to facilitate the mapping process. The semantic information is efficiently extracted by a fully convolutional neural network and rendered on a spherical projection of the laser range data. This computed semantic segmentation results in point-wise labels for the whole scan, allowing us to build a semantically-enriched map with labeled surfels. This semantic map enables us to reliably filter moving objects, but also improve the projective scan matching via semantic constraints. Our experimental evaluation on challenging highways sequences from KITTI dataset with very few static structures and a large amount of moving cars shows the advantage of our semantic SLAM approach in comparison to a purely geometric, state-of-the-art approach.
Calibrating Stiffness and Displacement of an Atomic Force Microscope using Self- Calibratable Micro-Electro-Mechanical Systems: Theoretical Study

We provide a theoretical study on the calibration of an atomic force microscope (AFM) using Micro-ElectroMechanical Systems (MEMS). The method we propose uses our self-calibratable MEMS technology to traceably measure the AFM cantilever stiffness and displacement. The calibration of displacement includes measuring the change in optical sensor voltage per change in displacement, or optical level sensitivity (OLS), and the calibration of stiffness along with displacement yields an accurate measurement of force. Calibrating the AFM is important because the AFM has been a most important tool for nanotechnologists for over two decades, yet the accuracy of the AFM has been largely unknown. Previous efforts to calibrate the AFM such as a thermal vibration method, an added weight method, and a layout geometry method are about 10% uncertain. As a consequence such AFM measurements yield about 1 significant digit of accuracy. What is new and different about our method is that we use MEMS, with traceably-calibrated force, stiffness, and displacement, as a sensor to calibrate the displacement reading and cantilever stiffness of the AFM. And our method is practical, easy to use, and can be fabricated in a standard SOI process. In this study we propose a general MEMS design, and provide accuracy, sensitivity, and uncertainty analyses.
WirelengthMinimization in Partitioning and Floorplanning Using Evolutionary Algorithms

Minimizing the wirelength plays an important role in physical design automation of very large-scale integration (VLSI) chips. The objective of wirelength minimization can be achieved by finding an optimal solution for VLSI physical design components like partitioning and floorplanning. In VLSI circuit partitioning, the problem of obtaining a minimum delay has prime importance. In VLSI circuit floorplanning, the problem of minimizing silicon area is also a hot issue. Reducing the minimum delay in partitioning and area in floorplanning helps to minimize the wirelength. The enhancements in partitioning and floorplanning have influence on other criteria like power, cost, clock speed, and so forth. Memetic Algorithm (MA) is an Evolutionary Algorithm that includes one or more local search phases within its evolutionary cycle to obtain the minimum wirelength by reducing delay in partitioning and by reducing area in floorplanning. MA applies some sort of local search for optimization of VLSI partitioning and floorplanning. The algorithm combines a hierarchical design technique like genetic algorithm and constructive technique like Simulated Annealing for local search to solve VLSI partitioning and floorplanning problem. MA can quickly produce optimal solutions for the popular benchmark.
RHIZOBIAL INOCULATION FOR IMPROVING GROWTH PHYSIOLOGY , NUTRITION AND YIELD OF MAIZE UNDER DROUGHT STRESS CONDITIONS

Water scarcity is a potential effector restraining crop yield and economic returns to the farmers. This situation may be rescued by inoculating drought tolerant rhizobia owing to their plant growth promotion attributes and high root colonization efficiency. A pot experiment was conducted in sandy clay loam soil to assess the potential of four drought tolerant rhizobial strains Rhizobium phaseoli-RS-1, R. phaseoli-RS-3, Mesorhizobium ciceri-RS-8, and M. ciceri-RS-12 for ameliorating drought impact in maize. The stress was applied at five leave (vegetative) and silking (reproductive) stages. Rhizobial strain RS-8 significantly (p≤0.05) decreased electrolyte leakage and increased root/shoot dry biomass, 100-grain weight and ultimately the grain yield in normal and drought condition compared to respective uninoculated control. Differential response of rhizobial inoculation was observed on physiological characters and plant nutrient uptake under normal and drought condition, however, RS-1 and RS-8 was more promising for improving chlorophyll contents, photosynthetic/transpiration rate, intrinsic water use efficiency, stomatal/mesophyll conductance, relative water contents and nutrient uptake in maize subjected to normal and drought conditions. Moreover, root colonization capability of RS-1 (5.52×10 CFU cm root) and RS-8 (5.89×10 CFU cm root) was higher than control (2.3×10 CFU cm root) and other strains under normal irrigation. Similarly, higher root colonization efficiency of RS-1 and RS-8 was observed under drought stress which seemed to improve plant yield by modulating physiological characters and nutrient uptake in stress conditions. Thus, the results are encouraging in the utilization of rhizobial strains (RS-1, RS-8) as biofertilizer for sustainable production of maize under water deficit conditions.
Personalizing a parenting app

The present study set out to personalize a digital library aimed at new parents by reordering articles to match users’ inferred interests. The interests were inferred from reading behavior as well as parenting styles measured through surveys. As prior research has shown that parenting styles are related to how parents take care of their children, these styles are likely to be related to what content a parent is interested in. The present study compared personalization based on parenting styles against other types of personalization. We conducted a user study with 106 participants, in which we compared the effects of four different approaches of personalization to our users’ reading behavior and user experience: a non-personalized baseline, personalization based on reading behavior, personalization based on parenting styles measured through surveys, and a hybrid personalization based on both reading behavior and parenting styles. We found that while the reading behavior was not signiﬁcantly inﬂuenced by different types of personalization, participants had a better user experience with our survey-based approach. They indicated they perceived a higher level of personalization and satisfaction with the system, even though in terms of objective metrics this approach performed worse.
Facial Keypoints Detection with Deep Learning

The facial keypoints detection is a challenging task due to the large variation of facial features, the change in 3D viewing angle, and difference in size and position of the face. Over the years, researchers have proposed a variety of algorithms such as combining multiple weak classifiers in cascade. However, a lot of work still needs to be done to further improve the detection accuracy and to accommodate for extreme cases. In this project, we proposed to use deep convolutional neural networks to locate the facial keypoints. Specifically, we experimented with LeNet, VGGNet and a 14-layer CNN on the Kaggle dataset. We also adopted image augmentation techniques to further increase the training set size. Finally, we were able to achieve a MSE of 3.02 with the VGGNet. The result indicated that deep CNNs have fairly good performance for the facial keypoints detection task.
Mollusk communities differ between microenvironments within a shallow lake in the Pampean Region , Argentina

The aim of this study is to compare the faunistic mollusk composition at a local scale, in different sites within a shallow lake, and to evaluate the relation between abundance and richness of mollusks and the environmental variables. The distribution of the mollusks within the water body was patchy but not random. Three of the sites were deeper, mainly dominated by emergent macrophytes and were characterized by the dominance of the gastropods Heleobia parchappii, Physa acuta and Uncancylus concentricus. In contrast, the other two sites were dominated by Biomphalaria peregrina and the bivalve Musculium argentinum, and were characterized by lower depth and pH, and higher vegetation diversity and water temperature. This study evidences the patchiness of freshwater mollusk species in a Pampean shallow lake, where environmental factors partially explain the local distribution within the lake. [
Occupational Experience , Wages and Mobility : Patterns in the Danish data ∗ Fane Groes

In this paper we present how occupational tenure relates to wage growth and occupational mobility in Danish data. We show that the Danish data produces qualitatively similar results as found in U.S. data with respect to an increase in average wages when experience in an occupation increases. In a sample of full time private employed, the first five years of experience in an occupation increases average wages with 8% to 15%, conditional on firm and industry tenure. We further show that the probability of switching occupation declines with experience in the occupation and that the declining hazard also is true for workers switching occupation and firm. After five years of experience in an occupation the average probability of switching any type of occupation, including occupation and firm switches, has fallen from 25% to 12%. ∗First version: March 2008. This version: May 2010. This paper has benefitted from many discussions with Philipp Kircher and Iourii Manovskii and is part of a joint project we have on occupational mobility. We would like to thank Martin Browning, Mette Ejrnæs and seminar participants at the University of Maryland, the 2008 Copenhagen Microeconometrics Summer Workshop and the Search & Matching workshop at the University of Pennsylvania for their comments.
Recovering Wind-induced Plant Motion in Dense Field Environments 3 via Deep Learning and Multiple Object Tracking 4 5 6

32 Wind-induced plant motion is an important feature of most agricultural systems yet it remains 33 understudied. This is partly due to the complexity of the field environment; though image sequences 34 showing plant motion are readily available, the cultivation of crop plants in dense field stands means 35 that detecting features and characterising their general movement traits is extremely difficult to 36 achieve. Here we present a robust method for characterising motion in field grown wheat plants 37 (Triticum aestivum) from time-ordered sequences of RGB images. A dataset of 290 images was 38 collected and annotated for ear tips from which a series of crops and augmentations were applied to 39 increase variation and resolution when training a convolutional neural network (CNN). This approach 40 enables the detection of wheat ears in the field without the need for camera calibration or a fixed 41 imaging position. Videos of wheat plants moving in the wind were also collected and split into their 42 component frames. Ear tips were detected using the trained network, then tracked between frames 43 using a novel probabilistic tracking algorithm to approximate movement. This data can be used to 44 characterise key movement traits such as periodicity. To our knowledge this is the first example of 45 tracking of plant features in order to obtain more detailed static plant properties and could form the 46 basis of new methodologies for assessing plant structure and function in the field; with automated data 47 extraction possible for informing lodging models, breeding programmes and linking movement 48 properties to canopy light distributions and dynamic light fluctuation. 49
PeX: A Permission Check Analysis Framework for Linux Kernel

Permission checks play an essential role in operating system security by providing access control to privileged functionalities. However, it is particularly challenging for kernel developers to correctly apply new permission checks and to scalably verify the soundness of existing checks due to the large code base and complexity of the kernel. In fact, Linux kernel contains millions of lines of code with hundreds of permission checks, and even worse its complexity is fast-growing. This paper presents PeX, a static Permission check error detector for LinuX, which takes as input a kernel source code and reports any missing, inconsistent, and redundant permission checks. PeX uses KIRIN (Kernel InteRface based Indirect call aNalysis), a novel, precise, and scalable indirect call analysis technique, leveraging the common programming paradigm used in kernel abstraction interfaces. Over the interprocedural control flow graph built by KIRIN, PeX automatically identifies all permission checks and infers the mappings between permission checks and privileged functions. For each privileged function, PeX examines all possible paths to the function to check if necessary permission checks are correctly enforced before it is called. We evaluated PeX on the latest stable Linux kernel v4.18. 5 for three types of permission checks: Discretionary Access Controls (DAC), Capabilities, and Linux Security Modules (LSM). PeX reported 36 new permission check errors, 14 of which have been confirmed by the kernel developers.
A Comparative Study of Secondary School Students ’ Performance in Commerce and ICT in Zambian Secondary Schools . A case Study of Selected Urban Schools of Lusaka District and Rural Schools of Chongwe District

This study assesses and compares the performance of students studying Commerce and ICT in their various Departments. The study sought to ascertain the relationship between the performance of students in Commerce and ICT. This was with a view of ensuring better performance in the two subjects. This study also focuses attention on possible ways of improving the performance of the students in the afore-mentioned subjects. It also suggests ways by which their performance in the said subjects could be improved. The study considered some students’ results in the said subjects over a period of two years (between 2016 and 2017). The collection of data was by the use of students’ results and questionnaire that were administered randomly to a selected sample population of some students. For this study, sixty students were randomly selected in Business Studies Department while fifteen students were purposely selected in Mathematics Department. Interviews were conducted by the teachers in charge of those subjects with above seven years of experience in teaching these subjects and some observations were also employed as secondary instruments. The data collected were analysed using simple percentages. Opportunities should be given to teachers for professional training on their subject disciplines, teaching techniques and organizational techniques which could be achieved through workshops, seminars, internet browsing and extensive reading for personal development. The findings show that students performed better in ICT subjects than in Commerce subjects.
ADBI Working Paper Series THE GENDER GAP IN PEER-TO-PEER LENDING: EVIDENCE FROM THE PEOPLE’S REPUBLIC OF CHINA

This paper documents and analyzes the gender gap in the online credit market. Using data from Renrendai, a leading peer-to-peer lending platform in the People’s Republic of China (PRC), we show that lending to female borrowers is associated with better loan performance, including a lower probability of default, a higher expected profit, and a lower expected loss than for their male peers. However, despite the higher creditworthiness, we don’t find any measurable gender impact on funding success rate, meaning that female borrowers have to compensate lenders by providing higher profitability to achieve a similar funding probability to their male peers. This evidence indicates the existence of a gender gap that discriminates against female borrowers. Further analysis implies that this gender gap is independent of the amount of information disclosed by borrowers.
Epidemiology of Acute Watery Diarrhea Outbreak and Challenges of Control — Afar , Ethiopia , 2009

Acute watery diarrhea (AWD) is becoming a big problem in Ethiopia. The aim was to rapidly investigate the outbreak epidemiologically and guiding response activities in the affected districts of Afar from April-June 2009. A line list and case register of districts were reviewed as per the world health organization case definition. 31 cases and 23 controls were interviewed with a structured questionnaire. Observation of case treatment centers and investor camps was made using checklist. Stool and drinking water samples were also collected, transported and examined as per standard microbiologic procedures. Then analysis was done using EPI Info version 3.5. 1. A total of 1,076 cases and 48 deaths were reviewed with an attack rate of 0.9% and case fatality rates of 4.4%. The majority [87.8% (945)] of cases were males. Hand washing after latrine usage (OR = 0.13, p= 0.03), unsanitary latrine (OR = 10.5, P-value= 0.001), contact with a case (OR = 200, P-value= 0.001) and visiting a place which has similar illness (OR=33.6, P=0.001) shown statistically significant association. Vibrio cholera 01 serotype Inaba and Escherichia coli were isolated from 89 % (9) of stool and 100 % (4) of drinking water samples respectively. V. cholera 01 serotype Inaba was confirmed as etiologic agent in all districts. Therefore, provision of safe drinking water supply and raising community awareness about hygienic practices to control diarrheal disease is necessary.
Concept for a membrane DBR laser using active/passive regrowth

Citation for published version (APA): Pogoretskii, V. G. , Higuera Rodriguez, A. , van Veldhoven, P. J., Tol, van der, J. J. G. M. , Heiss, D. , & Smit, M. K. (2015). Concept for a membrane DBR laser using active/passive regrowth. In P. Kockaert, P. Emplit, S-P. Gorza, & S. Massar (Eds.), Proceedings of the 20th Annual Symposium of the IEEE Photonics Benelux Chapter, 26-27 November 2015, Brussels, Belgium (pp. 125-128). Brussels: OPERA-photonics, Brussels School of Engineering.
Spatial disaggregation of catchment scale fluxes

Topography is an important physical driver of the hydrologic response of a catchment. Several topographic wetness indices have been used to relate different landscape elements to catchment behaviour. However, these methods do not take into account the effects of landuse, soils and climate without the use of a fully distributed model. A new downscaling method is presented that can be applied easily to spatially disaggregate catchment scale fluxes by taking into account the effects of topography, landuse, soils and climate. Total runoff at the outlet of the catchment can be partitioned into surface runoff and groundwater discharge. The surface runoff component can then be attributed to different landscape elements by combining the following using a downscaling procedure that conserves the mass under current conditions: (a) runoff efficiency for each landuse and soil type, (b) area under each landuse, and (c) topographic location. The runoff efficiency is defined as the ratio of long-term mean annual runoff comprising overland flow, shallow sub-surface flow and lateral throughflow from a given landuse compared with that from areas under annual pasture. Using an analogous procedure and by replacing runoff efficiency with the recharge efficiency, groundwater flow from the catchment can also be attributed to different landscape elements. The runoff and recharge efficiencies can be obtained either from the current knowledge of farming systems or from process modelling or both. The method can then be used to evaluate the effects of landuse change on flow at the catchment outlet. Implementation of this method is demonstrated on the Little River catchment located in the Macquarie Basin, New South Wales.
Characterization of a simulated minor merger resembling Gaia-Enceladus

The second Gaia data release (Gaia Collaboration et al., 2018a) has provided evidence for a merger event roughly 10 Gyr ago with an object named Gaia-Enceladus (Helmi et al., 2018). A previous simulation by Villalobos and Helmi (2008, 2009) produced a similar velocity distribution of halo stars near the Sun as seen in the Gaia data. In this bachelor thesis I continue this simulation for 10 Gyr in an attempt to characterize stars of Gaia-Enceladus, which accounts for a large fraction of the galactic halo and possibly triggered the formation of the thick disk. The aim of the thesis is to help interpret the observations and to provide means to find likely members of Gaia-Enceladus in the Gaia data, especially at large distances from the Sun. I find that the characteristic kinematics of the accreted stars are maintained through the extension of the simulation and still show similarities to the various features seen in the Gaia data. These features can be understood well when analyzing the angular momentum and eccentricity as they are correlated to the initial position of the stars, and to the mass loss history.