Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing, Characterization and Erosion Wear Behaviour of Coir Fiber Reinforced Epoxy Composites

Now-a-days, natural fibers have been receiving considerable attention as the substitute for synthetic fiber reinforcement such as glass in plastics. Among various fibers, coir is most widely used natural fiber due to its advantages like easy availability, low cost, low density, low production cost and satisfactory mechanical properties.The objective of the present research work is to study the physical, mechanical, water absorption and erosion wear behaviour of coir fiber reinforced epoxy composites filled with Al2O3 filler. Twenty different samples without filler and twenty samples with constant filler content of 10 wt% were prepared by varying the length of the fiber (3 mm, 6 mm, 9 mm, 12 mm and 15 mm) and content of fiber (5 wt%, 10 wt%, 15 wt% and 20 wt%) using hand lay-up technique. The density, hardness, tensile strength, tensile modulus, flexural strength, impact energy and percent of water absorption of the composites were analyzed. The erosion wear of these composites have been evaluated at different impingement angles (30°, 45°, 60°, 75° and 90°) and at different impact velocities (48m/s, 70m/s, 82m/s and 109m/s). The effect of fiber length and content on the properties of composites is also analyzed. A comparison has been made between composites with and without Al2O3 filler. It has been observed that composites filled with Al2O3 filler shows better mechanical and wear properties as compared to composites without filler. A multi-criteria decision making approach called TOPSIS is also used to select the best material from a set of alternatives. The morphology of eroded surfaces is examined by using scanning electron microscopy (SEM) and possible wear mechanisms are discussed.
Efficacy of different spinal nerve roots for neuromodulation of micturition reflex in rats

Electrical stimulation of peripheral nerves controlling the bladder is an alternative, nondestructive medical treatment for urinary incontinence and retention. In this study, we aimed to identify the most efficient sensory and motor spinal nerve roots involved in the micturition reflex. Unilateral L5-S2 dorsal and ventral roots were electrically stimulated, and bladder reflex contractions were recorded under isovolumetric conditions. Repeated stimulation of the L6 and S1 dorsal roots not only abolished bladder reflex contractions but also induced a poststimulation inhibitory effect, whereas repeated stimulation of the L5 and S2 dorsal roots had no effect. Only the L6 ventral root directly caused bladder contraction when ventral roots L5-S2 were stimulated in sequence. Upon retrograde tracing using pseudorabies virus (PRV), the sacral parasympathetic nucleus of the L6 segment had more PRV-positive cells than the other segments, though the S1 segment of the dorsal root ganglia had the highest density of PRV-positive neurons. These results suggest the L6 ventral root is most efficient in producing detrusor muscle contraction, and the S1 dorsal root best inhibits the micturition reflex.
Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers

With the rapid development of mobile devices and the crowdsourcing platforms, the spatial crowdsourcing has attracted much attention from the database community, specifically, spatial crowdsourcing refers to sending a location-based request to workers according to their positions. In this paper, we consider an important spatial crowdsourcing problem, namely reliable diversity-based spatial crowdsourcing (RDB-SC), in which spatial tasks (such as taking videos/photos of a landmark or firework shows, and checking whether or not parking spaces are available) are time-constrained, and workers are moving towards some directions. Our RDB-SC problem is to assign workers to spatial tasks such that the completion reliability and the spatial/temporal diversities of spatial tasks are maximized. We prove that the RDB-SC problem is NP-hard and intractable. Thus, we propose three effective approximation approaches, including greedy, sampling, and divide-and-conquer algorithms. In order to improve the efficiency, we also design an effective cost-model-based index, which can dynamically maintain moving workers and spatial tasks with low cost, and efficiently facilitate the retrieval of RDB-SC answers. Through extensive experiments, we demonstrate the efficiency and effectiveness of our proposed approaches over both real and synthetic datasets.
A battery of 12 microsatellite markers for genetic analysis of the Leishmania (Viannia) guyanensis complex

SUMMARY We used 12 microsatellite markers developed for Leishmania braziliensis to genotype 28 strains of the main species of the Leishmania guyanensis complex (i.e. L. guyanensis and L. panamensis) collected in Ecuador and Peru. The important heterozygote deficits observed in these populations are similar with the previous data obtained in L. braziliensis and raise again the debate on the reproductive mode of these protozoan parasites. The data showed genetic polymorphism and geographical differentiation giving information on population structure of the L. guyanensis complex. Regarding the two species, this study enhances again the debate on the taxonomic status of the different isolates belonging to L. guyanensis s.l. since the results showed substantial heterogeneity within this species complex. In conclusion, this study increases the number of available microsatellite loci for L. guyanensis species complex and raises fundamental biological questions. It confirms that microsatellite markers constitute good tools for population genetic studies on parasites of this complex.
A Machine Learning Approach To Identify Hydrogenosomal Proteins in Trichomonas vaginalis

ABSTRACT The protozoan parasite Trichomonas vaginalis is the causative agent of trichomoniasis, the most widespread nonviral sexually transmitted disease in humans. It possesses hydrogenosomes—anaerobic mitochondria that generate H2, CO2, and acetate from pyruvate while converting ADP to ATP via substrate-level phosphorylation. T. vaginalis hydrogenosomes lack a genome and translation machinery; hence, they import all their proteins from the cytosol. To date, however, only 30 imported proteins have been shown to localize to the organelle. A total of 226 nuclear-encoded proteins inferred from the genome sequence harbor a characteristic short N-terminal presequence, reminiscent of mitochondrial targeting peptides, which is thought to mediate hydrogenosomal targeting. Recent studies suggest, however, that the presequences might be less important than previously thought. We sought to identify new hydrogenosomal proteins within the 59,672 annotated open reading frames (ORFs) of T. vaginalis, independent of the N-terminal targeting signal, using a machine learning approach. Our training set included 57 gene and protein features determined for all 30 known hydrogenosomal proteins and 576 nonhydrogenosomal proteins. Several classifiers were trained on this set to yield an import score for all proteins encoded by T. vaginalis ORFs, predicting the likelihood of hydrogenosomal localization. The machine learning results were tested through immunofluorescence assay and immunodetection in isolated cell fractions of 14 protein predictions using hemagglutinin constructs expressed under the homologous SCSα promoter in transiently transformed T. vaginalis cells. Localization of 6 of the 10 top predicted hydrogenosome-localized proteins was confirmed, and two of these were found to lack an obvious N-terminal targeting signal.
Determination of Metal Elements in Wine Using Laser-Induced Breakdown Spectroscopy (LIBS)

We developed a method for sensitive elemental analysis of wines using laser-induced breakdown spectroscopy (LIBS). In order to overcome the inefficiency of direct ablation of bulk wine (an organic liquid), a thin layer of wine residue was prepared on a metallic target according to an appropriated heating procedure applied to an amount of liquid wine dropped on the target surface. The obtained ensemble was thus ablated. Such a sample preparation procedure used a very small volume of 2 mL of wine and took only 30 min without reagent or solvent. The results show the detection of tens of metal and non-metal elements including majors (Na, Mg, K, Ca), minors, and traces (Li, B, Si, P, Ti, Mn, Fe, Cu, Zn, Rb, Sr, Ba, and Pb) in wines purchased from local supermarkets and from different production places in France. Commercially available wines were then spiked with certified standard solutions of Ti and Fe. Three series of laboratory reference samples were thus prepared using three different wines (a red wine and a white wine from a same production region and a red wine from another production region) with concentrations of Ti and Fe in the range of 1–40 mg/L. Calibration graphs established with the spiked samples allowed extracting the figures-of-merit parameters of the method for wine analysis such as the coefficient of determination (R2) and the limits of detection and quantification (LOD and LOQ). The calibration curves built with the three wines were then compared. We studied the residual matrix effect between these wines in the determination of the concentrations of Ti and Fe.
Assessment of caries activity using the Calcivis® Caries Activity Imaging System

Objective: An adequate diagnosis of dental caries means not only assessment of the change and the spread of change in the lesion, but also making a decision concerning its possible activity. Caries activity is primarily assessed using visual-tactile criteria that help estimate the probability of a carious lesion to progress. The aim of the present study was to test the capability of a new approach to ascertain lesion activity by means of bioluminescence (CalcivisⓇ Caries Activity Imaging System, Calcivis) in-vitro. Subjects and Methods: 46 extracted permanent posterior teeth were included in the study (30 occlusal surfaces, 16 smooth surfaces). The investigation sites were classified by two examiners using ICDAS and NYVAD criteria for lesion activity (activity yes/no) and consensus score of each site was determined as reference value. The sites were photographed using a prototype Calcivis System and the images were evaluated by both examiners for the presence of activity (bioluminescence, blue spots at the investigation sites). Correlation of methods was calculated using Spearman's rank correlation coefficient (rs). Agreement between methods was assessed by kappa statistics. ROC curves were created for Calcivis and both visual methods and the areas under the Curve (AUC) were compared (α=0.05). Results: Significant positive correlation was found between Calcivis and the visual detection methods: rs ICDAS=1.0, rs Nyvad criteria=0.776 (p<0.001). Kappa-values were: Calcivis/ICDAS=1.0, Calcivis/Nyvad=0.78. AUC for Calcivis was 1.0 (ICDAS as reference value) and 0.89 (Nyvad criteria as reference value). No significant differences were observed between the AUCs (p=0.30). Conclusion: The in-vitro use of the bioluminescence method showed good agreement with visual findings in assessment of the activity of a carious lesion in the area of occlusal and smooth surfaces.
Research on image classification based on HP — Net convolutional neural networks

Based on the Caffe deep learning framework and the first convolution layer inversion operation, this paper presents a deep-learning framework, denoted as HP-Net, to achieve image classification problem, The HP-Net network consists of three convolution layers and max-pooling layers followed by three fully connected layers. The first convolution layer adopts the inversion operation to add the transmission of the effective feature information and uses a smaller convolution kernel to extract more texture features. Finally, the softmax classifier is employed to identify image classifications. In this method, we use a very efficient graphics processing unit implementation of the convolution operation to further reduce training time. The HP-Net model demonstrated better performance two real-world datasets than two related state-of-the-art approaches, CaffeNet and AlexNet.
CCODR: Routing optimization for DTN-based space networks in congestion control

Interplanetary Network (IPN) is divided into restricted networks because of the harshness of the network environment. Delayed Tolerance Network (DTN) is one of the approved limited network solutions. The static network topology model can't be used for DTN networks due to the frequent interruption of links. In the DTN network, the Contact Graph Routing (CGR) algorithm is widely used. The CGR algorithm is a local optimal routing algorithm. However, due to the shortcomings of the local routing algorithm, the EAODR algorithm is proposed. First, the Modified Temporal Graph (MTG) model is proposed to represent the dynamic topology of the satellite. Second, the global routing algorithm is proposed. But the interplanetary network, the link through the frequency and the link quality is bad, so to minimize the packet loss ratio has become the satellite DTN network key. We improved the Earliest Arrival Optimal Delivery Ratio (EAODR) algorithm, we will predict the congestion rate according to the satellite the history of the queue change rate to avoid congestion. When the entire network congestion is serious, we can take the packet dropping strategy. Discarding packets with low arrival ratio, to ensure the arrival ratio of the whole network. We base Congestion Control Optimal Delivery Ratio (CCODR) routing algorithm on the MTG model. Our results show that we can reduce the delay by CCDOR compared to EAODR.
Asymptotic close to optimal joint resource allocation and power control in the uplink of two-cell networks

In this paper, we investigate joint resource allocation and power control mechanisms for two-cell networks, where each cell has some sub-channels which should be allocated to some users. The main goal persuaded in the current work is finding the best power and sub-channel assignment strategies so that the associated sum-rate of network is maximized, while a minimum rate constraint is maintained by each user. The underlying optimization problem is a mixed integer non-linear problem which is not convex and does not yield a trivial solution. In this regard, to tackle the problem, using an approximate function which is quite tight at moderate to high signal to interference plus noise ratio (SINR) region, the problem is divided into two disjoint sub-channel assignment and power allocation problems. It is shown that having fixed the allocated power of each user, the sub-channel assignment can be thought as a well-known assignment problem which can be effectively solved using the so-called Hungarian method. Then, the power allocation is analytically derived. Furthermore, it is shown that the power can be chosen from two extremal points of the maximum available power or the minimum power satisfying the rate constraint. Numerical results demonstrate the superiority of the proposed approach over the random selection strategy as well as the method proposed in [3] which is regarded as the best known method addressed in the literature.
SceneSLAM: A SLAM framework combined with scene detection

Different sensors have different capacities and may even fail in different scenes. This will influence accuracy and reliability of SLAM systems utilizing those sensors. To enhance the robustness of SLAM systems, we present SceneSLAM in this paper, which is a novel extensible SLAM framework by combing different SLAM systems facilitated by a scene detection method. SceneSLAM can activate different SLAM modules automatically based on the result of scene detection and perform map fusion to achieve globally consistent localization and mapping. To verify the extendibility and effectiveness of SceneSLAM, we build a prototype system based on SceneSLAM to enhance the reliability of existing SLAM systems when the light condition changes dramatically. The prototype system runs on a TurtleBot robot equipped with a Kinect sensor. The experimental results show that SceneSLAM provides an effective solution to enhance the robustness of existing SLAM systems in dynamic environments by activating corresponding SLAM module based on the scene detection results. SceneSLAM provides efficient support to developing and implementation of a SLAM system with multiple SLAM modules and a scene detection module. Furthermore, we release the source code of our framework with our prototype system, so that it can be easily extended by other researchers.
Language � Independent Data � Oriented Grapheme

We describe an approach to grapheme to phoneme conver sion which is both language independent and data oriented Given a set of examples spelling words with their associated phonetic representation in a language a grapheme to phoneme conversion system is automatically pro duced for that language which takes as its input the spelling of words and produces as its output the phonetic transcription according to the rules implicit in the training data We describe the design of the system and compare its performance to knowledge based and alternative data oriented
EXPERIMENTAL DETERMINATION OF CUTTING SPEED INFLUENCE ON CUTTING SURFACE CHARACTER IN MATERIAL LASER CUTTING

In industrial practice the material laser cutting is extensively used for rather accurate and high-quality cutting of both metal and non-metal materials. The objective of the submitted paper is to point out direct relation between influence of cutting speed and surface character of material cut by laser. Cutting speed ranks among the most significant technological parameters in laser cutting and represents important parameter for the productivity of production process. The results of experimental measurements can be applied in practice.
Planar Photonic Crystals for Biosensing

Faculty of Applied Science & Engineering Edward S. Rogers Sr. Department of Electrical and Computer Engineering Master of Applied Science by Mohamed El Beheiry In this thesis, planar photonic crystals for optofluidic biosensing applications are analyzed. Planar photonic crystals are optically resonant structures which possess modal characteristics which can be exploited for biosensing applications. Sensing is achieved by detecting changes in refractive index due to analyte interactions in a sampled fluid. This work describes a broad study of photonic crystal slab sensors, with special consideration to biosensing. Outlined are considerations pertaining to sensing figures of merit, device fabrication, and performance. Results of simulations and device characterization indicate that planar photonic crystals possess sensing attributes similar or better than existing optically resonant refractive index sensors, such as surface plasmon resonance, grating, and interferometric waveguide sensors. Additionally, these photonic crystals can be patterned in large-areas which enable a simple light coupling scheme. All considered, their appeal as a biosensing solution is justified in the area of in vitro diagnostics.
Direct Comparison of the Enzymatic Characteristics and Superoxide Production of the Four Aldehyde Oxidase Enzymes Present in Mouse

Aldehyde oxidases (AOXs) are molybdoflavoenzymes with an important role in the metabolism and detoxification of heterocyclic compounds and aliphatic as well as aromatic aldehydes. The enzymes use oxygen as the terminal electron acceptor and produce reduced oxygen species during turnover. Four different enzymes, mAOX1, mAOX3, mAOX4, and mAOX2, which are the products of distinct genes, are present in the mouse. A direct and simultaneous comparison of the enzymatic properties and characteristics of the four enzymes has never been performed. In this report, the four catalytically active mAOX enzymes were purified after heterologous expression in Escherichia coli. The kinetic parameters of the four mouse AOX enzymes were determined and compared with the use of six predicted substrates of physiologic and toxicological interest, i.e., retinaldehyde, N1-methylnicotinamide, pyridoxal, vanillin, 4-(dimethylamino)cinnamaldehyde (p-DMAC), and salicylaldehyde. While retinaldehyde, vanillin, p-DMAC, and salycilaldehyde are efficient substrates for the four mouse AOX enzymes, N1-methylnicotinamide is not a substrate of mAOX1 or mAOX4, and pyridoxal is not metabolized by any of the purified enzymes. Overall, mAOX1, mAOX2, mAOX3, and mAOX4 are characterized by significantly different KM and kcat values for the active substrates. The four mouse AOXs are also characterized by quantitative differences in their ability to produce superoxide radicals. With respect to this last point, mAOX2 is the enzyme generating the largest rate of superoxide radicals of around 40% in relation to moles of substrate converted, and mAOX1, the homolog to the human enzyme, produces a rate of approximately 30% of superoxide radicals with the same substrate.
Determination of uranium isotope ratios using a liquid sampling atmospheric pressure glow discharge/Orbitrap mass spectrometer system.

RATIONALE The field of highly accurate and precise isotope ratio analysis, for use in nonproliferation, has been dominated by thermal ionization and inductively coupled plasma mass spectrometry. While these techniques are considered the gold standard for isotope ratio analysis, a downsized instrument capable of accurately and precisely measuring uranium (U) isotope ratios is desirable for field studies or in laboratories with limited infrastructure. METHODS The developed system interfaces the liquid sampling, an atmospheric pressure glow discharge (LS-APGD) ion source, with a high-resolution Exactive Orbitrap mass spectrometer. With this experimental setup certified U isotope standards and unknown samples were analyzed. The accuracy and precision of the system were then determined. RESULTS The LS-APGD/Exactive instrument measured a certified reference material of natural U (235 U/238 U = 0.007261) with a 235 U/238 U ratio of 0.007065 and a % relative standard uncertainty of 0.082, meeting the International Target Values for the destructive analysis of U. In addition, when three unknowns were measured and these measurements were compared with the results from an ICP multi-collector instrument, there were no statistical differences between the two instruments. CONCLUSIONS The LS-APGD/Orbitrap system, while still in the preliminary stages of development, offers highly accurate and precise isotope ratio results that suggest a potential paradigm shift in the world of isotope ratio analysis. Furthermore, the portability of the LS-APGD as an elemental ion source, combined with the small size and smaller operating demands of the Orbitrap, suggests that the instrumentation is capable of being field-deployable.
Acoustic contacting detection in robotic accurate assembly

In accurate assembly, small position uncertainties of robot end effector might result in large force and break fragile parts potentially. Contacting of assembly parts is a key information to terminate such procedure. Traditional way is to adopt strain gauge load cell to detect contacting. However, the drawbacks of this type of load cell is short lifetime and low sensitivity. In this paper, we presents an acoustic contacting detection including basic principle and feasibility studies. Finally, the proposed method is implemented in a demonstration assembly case.