Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation between Rheological and Adhesion Properties of Polyamide Hot Melt Adhesive Synthesized from Dimer Acid (Dilinoleic acid) and Ethylene Diamine

The temperature at which hot melt adhesives (HMAs) are applied is very important to be known, as it will strongly affect the rheology of the material, ultimately affecting the adhesion properties. In this study polyamide HMA was synthesized using high purity polymerized fatty acid (dimer acid or dilinoleic acid) and ethylenediamine, and characterized for mechanical, thermal, adhesion and rheological properties. Adhesion joint formation (lap and T-peel) and rheological characterization were performed at varied temperatures – 140, 155, 170, 185 and 200°C to understand the effect of temperature on the properties mentioned and also to correlate them. From the correlative study it was found that 170°C is the best temperature to apply this adhesive. However, it cannot be generalized for other HMAs as it depends on many factors like: molecular weight of the adhesive, molecular weight distribution, type of glue gun, additives added, raw material used to prepare the HMA etc. Too low temperature leads to improper wetting of the substrates, while too high temperature leads to the formation of cross-links in the adhesive leading to optimized temperature of 170°C.
Gyrokinetic simulations of electrostatic microinstabilities and turbulence with bounce-averaged kinetic electrons for shaped tokamak plasmas1

Nonlinear bounce-averaged kinetic theory[B. H. Fong and T. S. Hahm, Phys. Plasmas 6, 188 (1999)] is used for magnetically trapped electrons for the purpose of achieving efficient gyrokinetic simulations of Trapped Electron Mode (TEM) dominant microturbulence transport in shaped tokamak plasmas. Bounceaveraged kinetic equations extended to shaped plasma equilibria are implemented to a global nonlinear gyrokinetic code, Gyro-Kinetic Plasma Simulation Program (gKPSP)[J. M. Kwon et al., Nucl. Fusion 52, 013004 (2012)]. The newly implemented code gKPSP is then benchmarked. With bounce-averaged gyrokinetic gKPSP simulation, stabilizing effects of elongation on both ITG and TEM can be understood in terms of magnetic flux expansion leading to the effective temperature gradient R/LT (1 − E′)[P. Angelino et al., Phys. Rev. Lett. 102, 195002 (2009)] and poloidal wave length contraction at low field side resulting in the effective poloidal wave number kθρi/κ. Investigation of collisional effects on TEM using gKPSP demonstrates the parameter dependence of density gradient and electron temperature gradient. In nonlinear gKPSP simulations, plasma elongation is shown to reduce both electron and ion heat conductivities.
Scan Registration Using the Normal Distributions Transform and Point Cloud Clustering Techniques

As the capabilities of autonomous vehicles increase, their use in situations that are dangerous or dull for humans is becoming more popular. Autonomous systems are currently being used in several military and civilian domains, including search and rescue operations, disaster relief coordination, infrastructure inspection and surveillance missions. In order to perform high level mission autonomy tasks, a method is required for the vehicle to localize itself, as well as generate a map of the environment. Algorithms which allow the vehicle to concurrently localize and create a map of its surroundings are known as solutions to the Simultaneous Localization and Mapping (SLAM) problem. Certain high level tasks, such as drivability analysis and obstacle avoidance, benefit from the use of a dense map of the environment, and are typically generated with the use of point cloud data. The point cloud data is incorporated into SLAM algorithms with scan registration techniques, which determine the relative transformation between two sufficiently overlapping point clouds. The Normal Distributions Transform (NDT) algorithm is a promising method for scan registration, however many issues with the NDT approach exist, including a poor convergence basin, discontinuities in the NDT cost function, and unreliable pose estimation in sparse, outdoor environments. This thesis presents methods to overcome the shortcomings of the NDT algorithm, in both 2D and 3D scenarios. To improve the convergence basin of NDT for 2D scan registration, the Multi-Scale k-Means NDT (MSKM-NDT) algorithm is presented, which divides a 2D point cloud using k-means clustering and performs the scan registration optimization over multiple scales of clustering. The k-means clustering approach generates fewer Gaussian distributions when compared to the standard NDT algorithm, allowing for evaluation of the cost function across all Gaussian clusters. Cost evaluation across all the clusters guarantees that the optimization will converge, as it resolves the issue of discontinuities in the cost function found in the standard NDT algorithm. Experiments demonstrate that the MSKM-NDT approach can be used to register partially overlapping scans with large initial transformation error, and that the convergence basin of MSKMNDT is superior to NDT for the same test data. As k-means clustering does not scale well to 3D, the Segmented Greedy Cluster NDT (SGC-NDT) method is proposed as an alternative approach to improve and guarantee convergence using 3D point clouds that contain points corresponding to the ground of the environment. The SGC-NDT algorithm segments the ground points using a Gaussian Process (GP) regression model and performs clustering of the non ground points using a greedy method. The greedy clustering extracts natural features in the environment and generates Gaussian clusters to be used within the NDT framework for scan registration.
Local dimensions for Poincaré recurrences

Pointwise dimensions and spectra for measures associated with Poincar e recurrences are calculated for arbitrary weakly specied subshifts with positive entropy and for the corresponding special ows. It is proved that the Poincar e recurrence for a \typical" cylinder is asymptotically its length. Examples are provided which show that this is not true for some systems with zero entropy. Precise formulas for dimensions of measures associated with Poincar e recurrences are derived, which are comparable to Young's formula for the Hausdor dimension of measures and Abramov's formula for the entropy of special ows.
Application of potential flow methods to ship squat in different canal widths

This paper presents a comparison of numerical methods with model test results for squat (sinkage and trim) of a 1:75 KVLCC2 model in the Flanders Hydraulics Research towing tank, at a range of rectangular canal widths and depths. The numerical methods are the Linear-2D and Nonlinear-1D methods in ShallowFlow, the Double-Body method in HullWave and the Rankine-Source method in GL Rankine. Analysis of the model tests showed that in the narrowest canals, mass flux past the ship was not conserved, nevertheless it appears that the Nonlinear-1D method may give good results for the narrowest canals. The Linear-2D method was found to give good results in the widest canal, particularly at the shallowest water depth. The Rankine-Source method was found to give good results for the widest canal, particularly at high speed. The Double-Body method was found to give quite consistently good results across all conditions.
A LITERATURE SURVEY ON RECOMMENDATION SYSTEM BASED ON SENTIMENTAL ANALYSIS

Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are categorized into three techniques of recommender system, i.e.; collaborative filtering (CF), content based and context based. We have tried to find out the research papers related to sentimental analysis based recommender system. To classify research done by authors in this field, we have shown different approaches of recommender system based on sentimental analysis with the help of tables. Our studies give statistics, approximately trends in recommender structures research, and gives practitioners and researchers with perception and destiny route on the recommender system using sentimental analysis. We hope that this paper enables all and sundry who is interested in recommender systems research with insight for destiny.
BIOREMEDIATION OF A CRUDE-OIL POLLUTED AGRICULTURAL SOIL AT PORT HARCOURT, NIGERIA

A combination of treatments, consisting of the application of fertilizers and oxygen exposure, was evaluated in-situ during a period of six weeks. Conditions of a major spill were simulated by sprinkling crude-oil on experimental cells containing agricultural soil. The remedial treatments were then applied and the soil characteristics analyzed after set periods. Soil physicochemical parameters, such as moisture content, pH value, electrical conductivity as well as, organic-carbon and total-nitrogen contents showed distinct variations with time. The total heterotrophic bacteria (THB) count in all the treatment cells increased with time. The control cell, O, (which was not treated) indicated no signs of remediation within the study period. The hydrocarbon losses (50 to 95%) experienced in the five other treatment-cells revealed the effectiveness in degrading the hydrocarbon contaminant. The results of this study indicate that the application of increased concentrations of nutrients (by the application of fertilizers) lead to greater rates of biodegradation of petroleum-polluted agricultural soils.
An evaluation of the psychometric properties of the concept 5.2 Occupational Personality Questionnaire

Using three samples of applicant data, encompassing over 2300 participants, the Concept Model 5.2 Occupational Personality Questionnaire (OPQ) was examined for scale discriminability at the item, scale and factorial level. Item analysis and maximum likelihood factor analysis indicated that the OPQ questionnaire provided good, low complexity measurement on 22 out of the 31 scales. Nine exhibited poor signal-to-noise ratios, high item complexity indices, and insufficient number of keyed loadings on the appropriate factor. On the basis of the results below and from those reported by Matthews & Stanton (1994), it was argued that the test requires further development in conjunction with the revision of the psychological and measurement models specified as underlying its construction.
Screening of Microbes producing extracellular hydrolytic enzyme from corporation waste dumping site and house hold waste for the enhancement of bioremediation methods

Search for microorganisms capable of biodegradation is one of the extensive areas of research. Screening and Identification of extra hydrolytic enzyme producing microbes from soil samples of landfill area and households of Trivandrum city was carried out. The ability of the bacterial isolates to produce various hydrolytic enzymes was determined using the plate assay. Result showed that the collected sample contains microbes capable for producing such enzymes and those strain can be further utilised for the enhanced bioremediation methods.
Analysis of Flow of Control for Reverse Engineering of Sequence Diagrams

During software lifecycle, the design documentation and implementation often diverge. This is especially true in iterative development processes and in legacy systems. System enhancement based on inaccurate documentation may result in costly software design and implementation flaws. Consequently, reverse engineering of system design could be beneficial during enhancement and maintenance. Important aspects of software design are represented using UML sequence diagrams, which are considered to be one of the core design artifacts. Recent introduction of the next generation UML presents new challenges for reverse engineering of sequence diagrams. One such challenge is the mapping of the flow of control in the code to the UML sequence diagram primitives. The work presented here addresses this problem through a static analysis algorithm for representing flow of control in sequence diagrams. We analyze control-flow graphs and map them to the UML primitives. We also propose a series of transformations on the resulting structure that are intended to improve readability and comprehension of the diagrams. These transformations reduce nesting while preserving the meaning of the diagrams. The simplification of the diagrams makes them easier to read and comprehend. We present an experimental study that evaluates the practicality of our analysis on several Java library components and the benefits of the transformations in reducing nesting in reverse-engineered sequence diagrams.
Competitive strength of Australian swamp stonecrop (Crassula helmsii) invading moorland pools

We conducted two indoor experiments to test the competitive strength of the invasive plant Crassula helmsii in comparison to that of two native moorland species from northwest Europe, Littorella uniflora and Hypericum elodes in terrestrial conditions. In both experiments nutrient-poor moorland soil was used. The total cover of C. helmsii increased gradually in monocultures, until after 7–20 weeks a maximum of 12% in experiment 1 and 15–20% in experiment 2 was reached in the control conditions. Nitrogen content of C. helmsii plants was very low at the end of the latter experiment. Adding additional N had little effect in experiment 1, but in experiment 2 C. helmsii cover doubled. In the mixed cultures, C. helmsii fared worse than the native species. In experiment 1 the increase in cover was higher for both L. uniflora and H. elodes than in their monocultures, while in experiment 2 fresh weight at the end of the experiment was 3 times higher for L. uniflora and did not differ significantly between H. elodes and C. helmsii. The results indicate that the native species are better competitors for nutrients than C. helmsii due to their larger root system. No allelopathic effect of L. uniflora on C. helmsii growth was observed. These observations are discussed in the light of C. helmsii management in the field.
VARIATIONS IN REPETITION DURATION AND REPETITION NUMBERS INFLUENCES MUSCULAR ACTIVATION AND BLOOD LACTATE RESPONSE IN PROTOCOLS EQUALIZED BY TIME UNDER TENSION. Brief running head : REPETITION DURATION AND REPETITION NUMBERS AND MUSCULAR ACTIVATION AND BLOOD LACTATE RESPONSE

The aim of this study was to investigate the impact of protocols equalized by the time under tension (TUT), but composed of different repe tition durations and repetitions numbers, on muscle activation and blood lactate con centration. Twenty-two males with previous experience in resistance training performe d two training protocols (A and B) with the Smith machine bench press exercise, both w ith 3 sets, 3 minutes rest, and 60% of one repetition maximum (1RM). Protocol A con sisted of 6 repetitions with a 6s repetition duration for each repetition, while in P rotocol B the subjects performed 12 repetitions with a 3s repetition duration for each repetition. Muscular activation was measured in the anterior deltoid, pectoralis major, and triceps brachii muscles while performing the two protocols and the normalized roo t mean square of the electromyographic signal (EMGRMS) was calculated fo r each set. Blood lactate concentrations were measured during and up to 12 mi nutes after the completion of each protocol. The results showed that the EMGRMS o f all muscles increased during the sets and was higher in Protocol B when compared to Protocol A. Likewise, blood lactate concentrations also increased throughout th e sets and was higher in Protocol B both during and after the completion of each traini ng session. The data obtained in this study show that training protocols conducted with t he same TUT, but with different configurations, produce distinct neuromuscular and metabolic responses, so that, performing higher repetition numbers with shorter r epetition durations might be a more appropriate strategy to increase muscle activation and blood lactate concentration.
Fast Video Artistic Transfer via Motion Compensation

Techniques for conversion of natural video scenes into drawing-style videos are frequently used to produce animated movies. In the past, the conversion was manually performed, what demanded a lot of time and a high production cost. Recently, with the advancement of computer vision techniques and the development of new deep learning algorithms, 'drawing' can be automatically performed. Nevertheless, current `drawing' algorithms are computationally expensive and require a high processing time. In this letter, we present a simple, but effective `drawing' algorithm that is capable of reducing the processing time.
Toxicity Evaluation of Methanol Extract of Clitoria ternatea L . Leaf

The Clitoria ternatea (Fabaceae) root, seed, and leaf are commonly used in Ayurvedic medicine in Malaysia and Indonesia. The methanol leaf extracts of C. ternatea was tested for toxicity by means of brine shrimp lethality test and acute oral toxicity assay. In the brine shrimp lethality test, the leaf extract were non-toxic or showed weak lethality (LC 50 > 1 mg/ml) at the 6 h, 12 h and 24 h incubation period. Nevertheless, at the 48 h incubation time, the leaf extract exhibited moderate toxicity activity with LC 50 values of 0.49 mg/ml. In the acute toxicity study using mice, the median lethal dose (LD 50 ) of the extract was found greater than 2000 mg/kg, and we found no pathological changes by means of macroscopic examination of tissues of mice treated with the extract. We conclude that the C. ternatea leaf extract is not toxic in mice and brine shrimp.
The Role of NO/cGMP Signaling on Neuroinflammation: A New Therapeutic Opportunity

The nitric oxide/cyclic guanosine monophosphate (NO/cGMP) signaling appears to play a key role in inhibiting neuroinflammation and preventing the activation of a proapop totic pathway, thereby promoting neural cell survival. In addition, evidence indicates that cGMP/protein kinase G (PKG) pathway is involved in the modulation of glial cell activity. Phosphodiesterase 5 (PDE5), which hydrolyzes cGMP in the inactive form, 5ʹGMP, is present throughout the body and brain and has emerged as a potential thera peutic target for diseases related to neuroinflammatory and neurodegenerative pro - cesses, since their inhibition leads to accumulation of cGMP. The objective of this chapter is to review current knowledge of NO/cGMP signaling pathways on neuroinflammation and the potential therapeutic use of PDE5 inhibitors (PDE5-Is) in neurological diseases. The extensive, while recent, literature on the effects of PDE-Is on Alzheimer’s disease (AD), multiple sclerosis (MS), Parkinson’s disease (PD), Huntington’s disease (HD), and stroke has been reviewed. mutant huntingtin protein (mhtt) extended polyglutamine at huntingtin gene, intraneuronal events death. time, this either causes or contributes to neuroinflammation. downstream target BACE1, also leads to cleavage of amyloid precursor protein (APP), contributing to the formation of Aβ plaques. PDE5-Is induce a decrease in the activity of calpain, p25, and CDK5, with consequent decrease in protein aggregation. GSK3β is a kinase involved in the hyperphosphorylation of Tau. In addition, through the downstream target, cathepsin B, GSK3β leads to the formation of Aβ plaques. pAkt is a GSK3β inhibitor, modulating the pathway. PDE-Is increase Akt phosphorylation and decrease GSK3β activity and cathepsin B expression, which can contribute to control the protein aggregation. by PDE5-Is, which may be important for the control of leukocyte infiltration. It is possible that complex cross signaling is occurring, but although it has been demonstrated in inflammatory models, it has not been confirmed in preclinical studies with PDE5-Is in neurological diseases. For example, elevated levels of cGMP by NO may inhibit PDE3 activity, which leads to increased cAMP levels and PKA activation. PKA inhibits NF-κB transcription activity and, subsequently, the expression of downstream MCP-1 and VCAM-1. stress, which activate the initiator pro-caspase-9. Proapoptotic mitochondrial proteins, BH3- only members, activate other proapoptotic proteins, such as BAX, and antagonize antiapoptotic proteins, such as Bcl-2. Subsequently, the mitochondrial outer membrane is disrupted, and its permeability increases, resulting in cytochrome-c (Cyt-c) leakage into the cytosol. Cyt-c in the cytosol forms a complex with Apaf-1, called the apoptosome, which assists in auto-activation of initiator pro-caspase-9. Caspase-9 activates caspase-3, leading to apoptosis.
Building detection in VHR Satellite Imagery by using Fast ICA and MSER

Satellite imagery in the recent past has gone through numerous advancement. Different satellite sensors have been developed with the capability to capture the data at different scales from coarse to very fine. The finer resolution data provides detailed information which helps in improving the object detection for more number of land cover classes. Satellite imagery forms the backbone of remote sensing. Remote sensing has a wide range of applications in Earth sciences like geology, military, economic and humanitarian purposes. Urban remote sensing is useful for analysing and planning. Building detection is one of the most important aspects of urban remote sensing. Building footprint detection is very useful in wide range of applications like disaster management, urban planning, cartography, environment modeling, all require knowledge of man made structures. Even now, mapping of buildings is done using remote sensing based on visual interpretation or manual digitizing of digital images. These methods are tedious, time consuming, requires qualified people, therefore it has virtually no scope for real-time applications. This work presents an approach to automatic building detection from very high resolution (VHR) satellite images. The work includes discussion of various image processing techniques used and challenges faced with detection of different building models. Monocular satellite data is used for this work. Satellite images typically contain elements like development areas, vegetation, water bodies, barren land etc. Development areas include buildings, roads, pavements and other such man-made entities. The first task of building detection process is to remove the natural entities and focus on development regions. This task is realized using Independent Component Analysis (ICA). Three input planes derived from the LAB and LUV colorspace are used as input to the ICA which in turn converts them into three independent output planes. One of these output planes primarily contains man-made structure pixels and other two primarily contain vegetation and other natural entities. Development areas are detected using pixels obtained from the plane and appropriate thresholding. The only drawback of this technique is buildings are obtained in the form of individual pixels and as a result, object-level performance of the detection is not as good as its pixel-level performance. The second phase of this work builds on the learning of ICA based building detection. The candidate building pixels obtained through ICA are now used to extract maximally stable extremal regions (MSER) which are then filtered using geometric properties to obtain final candidate buildings. The technique is aimed at improving object-level performance. The achieved Precision of 80.64% and Recall of 83.65 % in case of object-level evaluation. The work offers an unsupervised building detection