Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical analysis of the texture effect on the hydrodynamic performance of a mechanical seal

The purpose of this paper is to analyze the effect of the main geometrical characteristics of texture on the hydrodynamic lubrication of a mechanical seal. A parametric study was carried out in order to improve the performance of a mechanical seal. The numerical model used in this study solves the Reynolds equation coupled with a mass conservative model which takes into account the cavitation phenomenon. It is shown that among the six dimple shapes tested herein, namely cylinder, square, triangle, truncated cone, truncated pyramid, and spherical cap, the triangular dimples placed symmetrically with respect to their bases are more effective for enhancing the hydrodynamic performance of the mechanical seal. The effect of the area and depth ratios is studied and optimized as well. The optimized solution is able to minimize friction and leakage under a range of operating conditions.
Transcriptome Analysis of Near-Isogenic Lines Provides Novel Insights into Genes Associated with Seed Low-Temperature Germination Ability in Maize (Zea mays L.)

Abstracts Maize originated from tropical regions and is extremely sensitive to low temperature during germination. Our previous work identified a major QTL, qp1ER1-1, for low temperature germination ability (LTGA) of maize. Here, we introgressed qp1ER1-1 from the tolerant line L220 into the sensitive line PH4CV to generate two near isogenic lines NIL220-3 and NIL220-25. When germinated under cold temperature for 25 days (Cold-25), the NILs showed similar seedling root length and shoot length to L220, but significantly higher than PH4CV. However, when germinated under cold temperature for 15 days (Cold-15) or under normal temperature (25 °C) for 3 days (CK-3), all lines showed similar seedling performance, indicating that introgression of qp1ER1-1 from L220 into PH4CV could improve LTGA of NIL220-3 and NIL220-25. The whole seedlings, including root and shoot, of Cold-15 and CK-3 were harvested for transcriptome analysis, when both stayed at a similar developmental stage. Dry seed embryo was sequenced as a non-germination control (CK-0). Compared with PH4CV, the tolerant line (L220, NIL220-3, and NIL220-25) specifically expressed genes (different expressed genes, DEGs) were identified for CK-0, Cold-15, and CK-3. Then, DEGs identified from Cold-15, but not from CK-0 or CK-3, were defined as tolerant line specifically expressed LTGA genes. Finally, 1786, 174, and 133 DEGs were identified as L220, NIL220-3, and NIL220-25 specifically expressed LTGA genes, respectively. Of them, 27 were common LTGA genes that could be identified from all three tolerant lines, with two (Zm00001d031209 and Zm00001d031292) locating in the confidence interval of qp1ER1-1. In addition, GO analysis revealed that L220 specifically expressed LTGA genes were majorly enriched in the cell division process and plasma membrane related categories. Taken together, these results provided new insight into the molecular mechanism of maize seed LTGA and facilitated the cloning of the qp1ER1-1 gene.
Model for Prediction of Student Grades using Data Mining Algorithms

There has been a rapid growth in the educational domain since education has become an important need. Data is collected in this domain which can be put to meaningful use to derive a lot of benefits to the students. Predicting student performance can help students and their teachers keep track of student progress. Mining Educational data helps to uncover invisible patterns, relationships, or trends in the unstructured data and helps in delivering logical and meaningful recommendations. Several kinds of research are being conducted across the world to analyze the data regarding student learning to identify the factors affecting performance and to provide support to students to help them improve. It is the objective of the proposed research to conduct a detailed study in the Sultanate of Oman regarding the existing toolsets, systems, and mode of data collection that are used currently in the Education sector for the prediction of Student Grades. Taking this as the baseline, later a model that will feature different prediction algorithms which are more accurate in predicting the grades of a student will be developed. The objective of this research is to understand the various predictive methods used to predict student performance and to propose a machine learning model to predict student grades.
SLAM Project - Long Term Ecological Study of the Impacts of Climate Change in the Natural Forest of Azores: II - A survey of exotic arthropods in disturbed forest habitats

Abstract Background The data we present consist of an inventory of exotic arthropods, potentially invasive, collected in exotic and mixed forests and disturbed native forest patches of the Azores Archipelago. The study was carried out between 2019 and 2020 in four islands: Corvo, Flores, Terceira and Santa Maria, where a total of 45 passive flight interception SLAM traps were deployed, during three to six consecutive months. This manuscript is the second contribution of the “SLAM Project - Long Term Ecological Study of the Impacts of Climate Change in the Natural Forest of Azores”. New information We provide an inventory of terrestrial arthropods belonging to Arachnida, Diplopoda, Chilopoda and Insecta classes from four Azorean islands. We identified a total of 21,175 specimens, belonging to 20 orders, 93 families and 249 species of arthropods. A total of 125 species are considered introduced, 89 native non-endemic and 35 endemic. We registered 34 new records (nine for Corvo, three for Flores, six for Terceira and 16 for Santa Maria), of which five are new for Azores, being all exotic possibly recently introduced: Dieckmanniellusnitidulus (Gyllenhal, 1838), Gronopsfasciatus Küster, 1851, Hadroplontustrimaculatus (Fabricius, 1775), Hypurusbertrandi (Perris, 1852) (all Coleoptera, Curculionidae) and Cardiocondylamauritanica Forel, 1890 (Hymenoptera, Formicidae). This publication highlights the importance of planted forests and disturbed native forest patches as reservoirs of potentially invasive arthropods and refuges for some rare relict endemic arthropod species.
Japanese Kofun in Maps given by a Spaceborne Digital Elevation Model based on Multiple Satellite Data Sets

Here we stress the possibility to use maps from Spaceborne Digital Elevation Models to analyze the locations of Kofun, the ancient tombs in Japan. The DEM used is that proposed by Yamazaki, Ikeshima,Tawatari, Yamaguchi, O'Loughlin, Neal, Sampson, Kanae and Bates, in 2017, and implemented at the web site https://it-ch.topographic-map.com . Abstract of Ref. [5] tells that “although the information about archaeoastronomy in Japan available to international audiences is limited, this does not mean that archaeoastronomy has never been attempted in Japan. On the contrary,” Ref. [5] “shows that a variety of archaeoastronomical research has been done in Japan”. In particular, as evidenced by the large bibliography, many studies have been performed concerning the orientations of ancient sites. Ref. in particular,
A New Method for the Visualization of Living Dopaminergic Neurons and Prospects for Using It to Develop Targeted Drug Delivery to These Cells

This is the first study aiming to develop a method for the long-term visualization of living nigrostriatal dopaminergic neurons using 1-(2-(bis(4-fluorophenyl)methoxy)ethyl)-4-(3-phenylpropyl)piperazine-BODIPY (GBR-BP), the original fluorescent substance, which is a derivative of GBR-12909, a dopamine uptake inhibitor. This method is based on the authors’ hypothesis about the possibility of specifically internalizing into dopaminergic neurons substances with a high affinity for the dopamine transporter (DAT). Using a culture of mouse embryonic mesencephalic and LUHMES cells (human embryonic mesencephalic cells), as well as slices of the substantia nigra of adult mice, we have obtained evidence that GBR-BP is internalized specifically into dopaminergic neurons in association with DAT via a clathrin-dependent mechanism. Moreover, GBR-BP has been proven to be nontoxic. As we have shown in a primary culture of mouse metencephalon, GBR-BP is also specifically internalized into some noradrenergic and serotonergic neurons, but is not delivered to nonmonoaminergic neurons. Our data hold great promise for visualization of dopaminergic neurons in a mixed cell population to study their functioning, and can also be considered a new approach for the development of targeted drug delivery to dopaminergic neurons in pathology, including Parkinson’s disease.
Green-Tech CAV: Next Generation Computing for Traffic Sign and Obstacle Detection in Connected and Autonomous Vehicles

In recent years, advanced technologies are used in automobiles, which make it simpler to drive on roads. However, driving is not trouble-free considering the unexpected hindrances and difficulty in recognizing traffic signs while driving at high speeds. Due to the advancement in technologies such as image recognition, several automated vehicles and techniques are developed to assist the drivers while driving. In this paper, an integrated intelligent system is designed using YOLO V3 neural architecture for recognizing the obstacles and visualizing the traffic sign through the input image from the camera of the moving vehicle. A Vehicular Adhoc Network (VANET) is being used with 5G connectivity to share the information to the other passing vehicles present in the vicinity. Apart from this, a notification is sent to the nearby centre for clearing any obstacle if found on roads during transportation. Real-time images of every possible obstacle such as a crack on roads along with traffic signs are trained using machine learning algorithms, thereby making the system more efficient and accurate. These techniques are developed in order to provide an pollution free environment and reduce accidents in roads with the concepts of green computing. The proposed automated system performs exemplary in recognizing the obstacle and traffic sign, making it easy for the drivers to drive more freely and reducing the pollution thereby producing a eco-friendly environment. According to the algorithms proposed in this paper, the results show that the algorithm used produces accurate results compared to the existing techniques.
Selected Construction Properties of Hybrid Epoxy Composites Reinforced with Carbon Fiber and Alumina

The purpose of this study is to investigate the impact of the introduction of powder modifi er into composite reinforced with carbon fabric on selected mechanical properties. The tests were performed on 16 groups of hybrid epoxy composites, including one reference group and 15 groups containing alumina with the grain size of F220, F240, F280, F320 and F360, added in the weight percent of 5%, 10% and 15%. This composite was made of certifi ed components designed for application in the aviation industry. Test results indicated that the increase of alumina content by weight caused thea decrease of strength of polymer composites in most tests. The value of the force transferred by the composite in the tensile test increased disproportionately to the cross section. It resulted in decreased strength. The addition of alumina impeded the super-saturation of the carbon fabric, which caused discontinuities in the matrix material.
Assessing the nonlinear decay of community similarity: Permutation and site‐block resampling significance tests

Modelling how community similarity decays with spatial distance is a key tool for the study of the processes behind community variation (beta diversity). Distance‐decay models are computed from pairwise metrics (i.e. community similarity and spatial distance between localities) and hence suffer from pairwise dependence in the data, precluding the use of standard significance tests. Besides, distance‐decay patterns are inherently nonlinear because similarity is bounded between 1 and 0. However, the only standard method to assess model significance under pairwise dependency is the Mantel test, which considers a linear model. To allow the use of nonlinear models in the assessment of distance‐decay patterns, we introduce here a nonlinear significance test combining a pseudo‐R2 statistic with either permutations or block‐site resampling with replacement.
A Vision-Aided Navigation System based on Optical Flow

This thesis presents design and comparison of a vision-aided uniformly semi-globally exponentially stable (USGES) nonlinear observer (NO) and a Multiplicative Extended Kalman Filter (MEKF) for estimation of attitude, gyro bias, position and velocity of a fixed-wing Unmanned Aerial Vehicle (UAV). The NO uses measurements from an Inertial Measurement Unit (IMU), a Global Navigation Satellite System (GNSS) receiver, and a video camera. The MEKF and the NO are evaluated with real world experimental data. Moreover two new NO representations are proposed. The proposed NOs have a computer vision (CV) system that is based on epipolar geometry, and hence independent of the depth in the images and the structure of the terrain being filmed. The first proposed NO utilizes a camera and the continuous epipolar constraint and is named Continuous Epipolar Optical Flow Nonlinear Observer (CEOF NO). The second proposed NO uses a camera and the epipolar constraint and is named Epipolar Optical Flow Nonlinear Observer (EOF NO). Experimental data from a UAV test flight show that the vision-aided NO is substantially less computational demanding than the MEKF. It is seen that the NO has similar performance as the MEKF by means of accuracy of the estimates. The NO and the MEKF estimates are compared with an Extended Kalman Filter (EKF) implemented on the onboard autopilot of the UAV. The results illustrate that the estimates of the states converge accurately to the correct values. Moreover simulated data show that the proposed observers have more robust CV than the previous developed vision-aided NO, yielding more accurate and robust performance.
Analysis and Computation of Solid Interfaces on the Meso Scale

The present thesis is concerned with the simulation of the loading behaviour of both hybrid lightweight structures and piezoelectric mesostructures, with a special focus on solid interfaces on the meso scale. Furthermore, an analytical review on bifurcation modes of continuum-interface problems is included. The inelastic interface behaviour is characterised by elastoplastic, viscous, damaging and fatigue-motivated models. For related numerical computations, the Finite Element Method is applied. In this context, so-called interface elements play an important role. The simulation results are reflected by numerous examples which are partially correlated to experimental data.
"Faking" is Neither Good Nor Bad, It Is a Misleading Concept: A Reply to Tett and Simonet (2021)

This paper comments on Tett and Simonet’s (2021) outline of two contradictory positions on job applicants’ self-presentation on personality tests labelled “faking is bad” (FIB) versus “faking is good” (FIG). Based on self-presentation theory (Marcus, 2009) Tett and Simonet assigned to their FIG camp, I develop the ideas of (a) understanding self-presentation from the applicant’s rather than the employer’s perspective, (b) avoiding premature moral judgment on this behavior, and (c) examining consequences for the validity of applicant responses with a focus on the intended use for, and the competitive context of, selection. Conclusions include (a) that self-presentation is motivationally and morally more complex than assumed by proponents of the FIB view; (b) that its consequences for validity are ambivalent, which implies that simple credos like “FIB” or “FIG” are equally unjustified; and (c) that the label “faking” shall be abandoned from the scientific inquiry on the phenomena at hand, as it contributes to prejudiced and often erroneous conclusions.
Electrode-free photonic electric field sensor on thin film lithium niobate with high sensitivity.

A high-sensitivity electrode-free photonic electric field (E-field) sensor is introduced on a thin film lithium niobate (TFLN) platform. An integrated Michelson interferometer, constructed by low-loss etched lithium niobite (LN) waveguide structures, is implemented as the sensing element. The sensing arms are designed in a spiral shape, which facilities a long interaction length with the external E-field in a small chip area. A minimal detectable E-field amplitude of 8.43 mV/m/Hz1/2 is experimentally obtained. The metal-electrode-free design of the proposed device avoids affecting the E-field to be measured and enables a vectorial response with a measured extinction ratio (ER) of 38 dB.
Phylogenetic analysis of Luciobarbus Heckel, 1843 and Barbus Cuvier & Cloquet, 1816 species in the Euphrates River (Turkey) based on mtDNA COI gene sequences

Natural fish species living in the Euphrates River System; It is subject to some pressures such as overfishing, competition with invasive species and habitat loss. As a result of these pressures, it leads to the decrease of endemic and native species. At the beginning of these species are the species belonging to the Barbus Cuvier & Cloquet, 1816 and Luciobarbus Heckel, 1843 genera, which have high economic importance. In this study, phylogenetic analysis of the species belonging to the genus Barbus Cuvier & Cloquet, 1816 and Luciobarbus Heckel, 1843, which live naturally in the Euphrates River, was carried out with mtDNA COI gene sequences. 17 fish samples belonging to five species from three localities belonging to the Euphrates river system (Turkey) were studied. Total DNA extraction was performed from muscle tissue using Commercial Kit. Then the mtDNA COI region was amplified by PCR and sequenced. Genetic distance values were calculated between 0.00201 and 0.15332, and it was determined that the closest species were L. xanthopterus and L. esocinus, and the most distant species were B. lacerta and A. grypus. In addition, phylogenetic analyzes of the target species were made and an phylogenetic tree was formed and the species were distinguished. In future studies, it is recommended to evaluate the data in this study, to determine the genetic characteristics of populations, and to carry out conservation studies at the population level.
Variable annuity pricing, valuation, and risk management: a survey

Variable annuity is arguably the most complex individual retirement planning product in the financial market. Its intricacy stems from a variety of product features including investment options, guaranteed benefits, withdrawal options, etc. In many ways, variable annuities can be viewed as traditional life and annuity products at the next level of sophistication with added financial options. Despite a significant amount of publications by practitioners and academics on the subject matter, there have been few research papers that systematically exploit the basic principles underlying the operation of variable annuities. This survey paper aims to fill in the gap in the literature for an overview of state-of-the-art technology and recent trends in the development of variable annuities.
Characterization of Constituents with Potential Anti-Inflammatory Activity in Chinese Lonicera Species by UHPLC-HRMS Based Metabolite Profiling

This study centered on detecting potentially anti-inflammatory active constituents in ethanolic extracts of Chinese Lonicera species by taking an UHPLC-HRMS-based metabolite profiling approach. Extracts from eight different Lonicera species were subjected to both UHPLC-HRMS analysis and to pharmacological testing in three different cellular inflammation-related assays. Compounds exhibiting high correlations in orthogonal projections to latent structures discriminant analysis (OPLS-DA) of pharmacological and MS data served as potentially activity-related candidates. Of these candidates, 65 were tentatively or unambiguously annotated. 7-Hydroxy-5,3′,4′,5′-tetramethoxyflavone and three bioflavonoids, as well as three C32- and one C34-acetylated polyhydroxy fatty acid, were isolated from Lonicera hypoglauca leaves for the first time, and their structures were fully or partially elucidated. Of the potentially active candidate compounds, 15 were subsequently subjected to pharmacological testing. Their activities could be experimentally verified in part, emphasizing the relevance of Lonicera species as a source of anti-inflammatory active constituents. However, some compounds also impaired the cell viability. Overall, the approach was found useful to narrow down the number of potentially bioactive constituents in the complex extracts investigated. In the future, the application of more refined concepts, such as extract prefractionation combined with bio-chemometrics, may help to further enhance the reliability of candidate selection.
Fill dynamics and sample mixing in the AirCore

Abstract. The AirCore is a long coiled tube that acts as a “tape recorder” of the composition of air as it is slowly filled or flushed. When launched by balloon with one end of the tube open and the other closed, the initial fill air flows out during ascent as the outside air pressure drops. During descent atmospheric air flows back in. I describe how we can associate the position of an air parcel in the tube with the altitude it came from by modeling the dynamics of the fill process. The conditions that need to be satisfied for the model to be accurate are derived. The extent of the mixing of air parcels that enter at different times is calculated so that we know how many independent samples are in the tube upon landing and later when the AirCore is analyzed.
Vulnerability Analysis of Metro Network Incorporating Flow Impact and Capacity Constraint after a Disaster

AbstractThis paper presents a modified topological vulnerability analysis for the metro network. The flow impacts and the capacity constraint are taken into account in this work. A node-based congestion is considered in the travel time model for the metro network. The logit-based path choice model is adopted to assign the flow in the network. Based on the present approach, the efficiencies of the metro network with either fully or partly damaged stations can be analyzed. The vulnerability of the Beijing metro network was studied based on the present method. The results show that the flow in the network plays an important role in the vulnerability analysis. Topological methods neglecting either the flow or the flow impacts would underestimate the vulnerability of the network. Both the magnitudes and patterns of origin-destination (O-D) demand influence on the assessment of vulnerabilities of the metro network and on the importance ranking of stations. Additionally, in a busy metro network the vulnerability.