Miracle-dz/UniFAR-FTUs huggingface dataset:
Isolation, Molecular and Biochemical Identification of Paraoxon-Metabolizing Pseudomonas Species

Seven soil borne bacterial isolates were collected from locations throughout the Houston metropolitan area. All isolatesproved capable of degrading the pesticide paraoxon to p-nitrophenol in carbon limited media and showed a high degree of tolerance to an environment exposed to increasing concentrations of the pesticide. A combination of 16S rRNA sequencing and fatty acid methyl ester analysis (FAME) analysis was used to identify the unknown bacterial species. Universal bacterial primers were used for 16S rRNA analysis to tentatively identify all seven isolates as species belonging to the genus Pseudomonas. Sequencing results coupled with FAME analysis resolved the species identity of the seven isolates as either Pseudomonas aeruginosa or Pseudomonas putida. The results of this study demonstrate that a combination of molecular and biochemical analysis provide sufficient resolution to identify paraoxon degrading microbial populations.
Diagnosis and identification of key issues of usability for reducing medication errors

At a unit of a hospital in the Brazilian city of Florianopolis, from the diagnosis to the administration of medicines in the inpatient, usability problems like errors were detected in the flow of medication as well as problems of greater severity. This paper aims to perform a diagnosis of usability in the inpatient unit of a teaching hospital in Florianopolis in order to identify the main problems in the flow of medication. As a method, the authors used literature review, field visits, assessments of usability principles and determination of the severity of the problems found. The step of lowest usability was the preparation, followed by the steps of dispensation, administration and prescription. As for severity, the similarity of names, colors and shapes of packages of drugs was identified as the most problematic. Beside the problems that involves the health care professionals, the hospital has problems like the environment and the products, like the packaging of medications. The usability diagnosis can help find ways to make the flow of medication more efficient and safe. Keywords: design, usability, medication errors.
Anthropometric Characteristics and Body Composition in Aikido Practitioners

Although aikido is a non-competitive martial art, it is recognised by SportAccord as worldwide practiced combat sport. There is a lack of scientific research in aikido and the influence of aikido practice on the human body is not known. This is the first study that presents anthropometric characteristics and body composition data in aikido practitioners. 33 adult male aikido athletes (age 36.5 +/- 9.6 years, height 178 +/- 8 cm, weight 81.2 +/- 10.1 kg) were measured. All subjects were divided from beginner to intermediate and advanced group, and were recruited from the Czech Aikido Federation which is officially recognised by the centre of aikido in Japan. As main methods, bio impedance and skinfold measurements were realized. In aikido, body composition does not play an important role compared to other martial arts. Average values are similar to reference of non-athlete population (BMI 25.6 +/- 2.7 kg/m, BF 17.18 +/- 5.18 %, FFM 65.71 +/- 7.69 kg, BSA 1.98 +/- 0.15 m(2)). Even though, aikido has positive effects on body composition, it does not have a high impact. Thus, aikido players should also gain benefits from other aspects of martial arts.
Flood Detection and Control Using Deep Convolutional Encoder-decoder Architecture

In most major cities, there are certain areas with insufficient sewage systems that are incapable of moving drainage water efficiently, especially in heavy rain scenarios. Using CCTV (Closed-circuit television) cameras in order to detect such water pooling requires human focus and attention, however, immediate action has to be taken to minimize the environmental impact of such incidents. Detecting flooding not only might help save people’s and city’s money and time, but also human lives as well. In this paper, we propose a deep learning approach to detect flooding. Using the method of image segmentation and state-of-the-art architecture, system is capable of detecting flooding early on.
Design of Output Codes for Fast Covering Learning using Basic Decomposition Techniques

We propose the design of output codes for solving the classification problem in Fast Covering Learning Algorithm (FCLA). For a complex multi-class problem normally the classifiers are constructed by combining the outputs of several binary ones. In this paper, we use the basic methods of decomposition; one per class (OPC) and Error Correcting Output Code (ECOC) with FCLA, binary to binary mapping algorithm as a base binary learner. The methods have been tested on Fisher’s well-known Iris data set and experimental results show that the classification ability is improved by using ECOC method.
Species Clarification of the Widely Cultivated Ganoderma in China Based on rDNA and FIP Gene Sequence Analysis

Among all Ganoderma species, only G. lucidum and G. sinense, have been approved to produce health products. Thus, it is important for Ganoderma production and trade to select a suitable genetic marker for Ganoderma species clarification. The ITS region of rDNA and FIP nucleotide sequences data were used for identification of twenty widely cultivated Ganoderma strains. The sizes of ITS1-5.8S-ITS2 region from different species of Ganoderma ranged from 452 to 474 bp, and those of the FIP nucleotide sequence were from 333 to 336 bp. Using the rDNA ITS region and FIP gene sequences data. and phylogenetic analysis revealed that these Ganoderma species belong to two groups i.e., red Ganoderma and black Ganoderma. In conclusion both the FIP and ITS1-5.8S-ITS2 genes can be used as genetic markers to distinguish two subgenera Ganoderma: Sect. Ganoderma and Sect. Phaenema, confirm widely cultivated Ganoderma, which mainly belong to subgenus Ganoderma. © 2016 Friends Science Publishers
Informational Diversity and Software Product Quality : The Intermediary Role of Conflict and Learning in Projects

Project teams are composed of a diverse collection of individuals to provide the necessary background and skills to complete an information system. The diversity within groups can be problematic from the standpoint of creating conflict that inhibits progress. A model is derived from theory that shows expected relationships among informational diversity (knowledge), conflict, and learning. All three of these variables are expected to impact eventual success of the project; with learning, informational diversity, and conflicts about the task being positive influences, but relationship conflicts being detrimental. A survey instrument composed of published metrics has been sent to project team members.
ESTABLISHING THE EMPIRICAL RELATIONSHIP BETWEEN NON-SCIENCE MAJORING UNDERGRADUATE LEARNERS' SPATIAL THINKING SKILLS AND THEIR CONCEPTUAL ASTRONOMY KNOWLEDGE

The astronomy education community has tacitly assumed that learning astronomy is a conceptual domain resting upon spatial thinking skills. As a first step to formally identify an empirical relationship, undergraduate students in a non-major introductory astronomy survey class at a medium- sized, Ph.D. granting, mid-western US university were given pre- and post-astronomy conceptual diagnostics and spatial reasoning diagnostics, Instruments used were the "Test Of Astronomy Standards" and "What Do You Know? " Using only fully matched data for analysis, our sample consisted of 86 undergraduate non-science majors. Students' normalized gains for astronomy surveys were low at . 26 and . 13 respectively. Students' spatial thinking was measured using an instrument designed specifically for this study. Correlations between the astronomy instruments' pre- to post-course gain scores and the spatial assessment instrument show moderate to strong relationships suggesting the relationship between spatial reasoning and astronomy ability can explain about 25% of the variation in student achievement.
Best Combination of Binarization Methods for License Plate Character Segmentation

A connected component analysis from a binary image is a popular character segmentation method but occasionally fails to segment the characters owing to image noise and uneven illumination. A multimethod binarization scheme that incorporates two or more binary images is a novel solution, but selection of binarization methods has never been analyzed before. This paper reveals the best combination of binarization methods and parameters and presents an in‐depth analysis of the multimethod binarization scheme for better character segmentation. We carry out an extensive quantitative evaluation, which shows a significant improvement over conventional single‐method binarization methods. Experiment results of six binarization methods and their combinations with different test images are presented.
An Investigation of the Relationship Between Cultural Orientations and Collaborative Learning and Its Implications on Higher Education

Bu calisma, ogrencilerin kulturel yonelimleri ve isbirlikli ogrenmeye iliskin davranissal niyetleri arasindaki iliskiyi incelemektedir. Bu baglamda, Planli Davranis Teorisi temel alinarak bir arastirma modeli onerilmis ve calismada test edilmistir. Arastirma modeli, isbirlikli ogrenmeye yonelik tutum ve oznel normlarin bireycilik-toplulukculuk yonelimleri ile aciklanabilecegini varsaymaktadir. Arastirma modelinin dogrulamasi icin 401 universite ogrencisinden anket yontemiyle toplanan veriler yapisal esitlik modellemesi kullanilarak analiz edilmistir. Sonuclar, toplulukculuk yonelimleri ile isbirlikli ogrenmeye yonelik tutum ve oznel normlar arasinda daha guclu bir iliski onermektedir. Bulgular, kulture ve calismanin temellendirildigi teoriye istinaden tartisilmistir. Arastirmaci ve uygulamacilara yonelik oneriler sunulmustur
On-demand Virtual Machine Placement in Infrastructure Cloud

Thanks to the virtualization technology, which allow sharing of virtual resources (hardware/software) among the cloud users. With the help of the virtualization technology, cloud computing provides on-demand computing services such as software, infrastructure, and platform as a service to users via the Internet. Virtual machine placement is a hot research topic, which is a process of mapping of virtual machines (VMs) on host machines (HMs) in the cloud. In our work, we propose a new multi-objective on-demand VM placement algorithm in infrastructure cloud referred as OVMP, in which VMs placed in real time with help of a resource-balanced model. The proposed algorithm maximize resource utilization in a balanced manner and also minimize the power consumption and resource wastage of infrastructure cloud. We test the proposed algorithm through simulation using Amazon EC2 Instances and simulation results show that the proposed algorithm performs better than the existing ones in terms of various performance metrics.
Design By Contract Methodology

Software components are still considered the weakest link when it comes to addressing reliability of a system. We argue that a systematic application of Bertrand Meyer's design by contract methodology improves reliability quite significantly. In the perspective of design by contract methodology, reliability is viewed as correctness and robustness. The concept of Reliability by Construction is dealt with in detail. Process steps to introduce or integrate design by contract methodology into existing SDLC of a product or system are discussed. The notion of sufficiently strong contracts is dealt with along with their advantages in defect prevention. Composition of function calls or services and the properties that contract specifications of successive functions(calls) need satisfy are stated. The process of contract refinement during successive phases of SDLC is discussed. Contract specification rules in the presence of inheritance in object-oriented programs are also discussed. Finally, we argue that design by contract methodology is a step towards zero-defect programming.
Photodynamic Efficiency of Xanthene Dyes and Their Phototoxicity against a Carcinoma Cell Line: A Computational and Experimental Study

The aim of this study is to assess the insights of molecular properties of the xanthene dyes [fluorescein (FL), Rose Bengal (RB), erythrosin B (EB), and eosin Y (EY)] to correlate systematically their photodynamic efficiency as well as their phototoxicity against a carcinoma cell line. The phototoxicity was evaluated by comparing the values of the medium inhibitory concentration (IC50) upon HEp-2 cells with the xanthene corresponding photodynamic activity using the uric acid as a chemical dosimeter and their octanol-water partition coefficient (). RB was the more cytotoxic dye against HEp-2 cell line and the most efficient photosensitizer in causing photoxidation of uric acid; nevertheless it was the only one characterized as being hydrophobic among the xanthenes studied here. On the other hand, it was observed that the halogen substituents increased the hydrophilicity and photodynamic activity, consistent with the cytotoxic experiments. Furthermore, the reactivity index parameters, electric dipole moment, molecular volume, and the frontier orbitals were also obtained by the Density Functional Theory (DFT). The lowest dipole moment and highest molecular volume of RB corroborate with its highest hydrophobicity due to heavy atom substituents like halogens, while the halogen substituents did not affect expressively the electronic features at all.
‘Effective Micro-organisms’ (EM): An Effective Plant Strengthening Agent for Tomatoes in Protected Cultivation

ABSTRACT The effect of treating organically grown tomato plants with Effective Micro-organisms (EM) combined with a stone dust-suspension (EM treatment) was tested in a pot experiment in a foliar tunnel at the University of Natural Resources and Life Sciences Vienna. In the EM treatment, the irrigation water was amended with EMa® and plants were treated with EM-stone dust-suspension. In the control treatment, tap water was used instead. In the EM treatment, bokashi, wheat bran fermented with EMa®, was additionally added to the planting substrate in both years. Only in 2007, the equivalent amount of wheat bran, composted without EMa® addition, was added to the substrate in the control as well. Inorganic N contents of the substrate were lower in the control in 2006, but increased when wheat bran compost was added in 2007. N mineralization at later stages of the experiment was higher in the EM treatment in 2007. Microbial biomass in the substrate was enhanced in both years. Total yield was higher and the number of fruits damaged by blossom-end rot was reduced in the EM-treated plants in 2007. The percentage of fruits in the best quality class was significantly higher in the EM treatment in both years. N, P and K contents in tomato leaves of the EM treatment were reduced, whereas the Fe content was higher. A more even N supply to the plants in the EM treatment, combined with the effect of a direct stone dust-application onto the plants, clearly increased plant yield and fostered plant health.
Identification of SSR markers using soybean (Glycine max) ESTs from globular stage embryos

Microsatellites, or simple sequence repeats (SSRs), in expressed sequence tags (ESTs) provide an opportunity for low cost SSR development. We looked for EST-SSRs in 403,511 ESTs (generated by 454 sequencing and representing 70,654 contigs and 52,082 singletons) from soybean globular stage embryos. Among 122,736 unique ESTs, 3,729 contained one or more SSRs. In total, 3,989 SSRs were identified including 304 mono, 1,374 di, 2,208 tri, 70 tetra, 13 penta and 20 hexanucleotide SSRs. Thirty three EST-SSRs were selected for primer design and polymorphism analysis using twenty soybean cultivars and one wild-type soybean. Successful amplification was obtained using 21 of these primer pairs, 11 of which detected polymorphisms in these soybean cultivars. These results demonstrated that 454 high throughput sequencing is a powerful tool for molecular marker development. From the 3,989 identified SSRs we expect to obtain a large number of makers with polymorphism among different soybean cultivars, which would be useful for analysis of genetic diversity and maker assisted selection in the soybean breeding programs.
Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies

In this paper, we present a generalisation of the Multilevel Monte Carlo (MLMC) method to a setting where the level parameter is a continuous variable. This Continuous Level Monte Carlo (CLMC) estimator provides a natural framework in PDE applications to adapt the model hierarchy to each sample. In addition, it can be made unbiased with respect to the expected value of the true quantity of interest provided the quantity of interest converges sufficiently fast. The practical implementation of the CLMC estimator is based on interpolating actual evaluations of the quantity of interest at a finite number of resolutions. As our new level parameter, we use the logarithm of a goal-oriented finite element error estimator for the accuracy of the quantity of interest. We prove the unbiasedness, as well as a complexity theorem that shows the same rate of complexity for CLMC as for MLMC. Finally, we provide some numerical evidence to support our theoretical results, by successfully testing CLMC on a standard PDE test problem. The numerical experiments demonstrate clear gains for sample-wise adaptive refinement strategies over uniform refinements.
Assessment of Information Needs in Manual Assembly

Large organizations are growing into even larger players, treating several markets around the globe, often leading to increase in product ranges in order to satisfy local markets. This has the risk of driving variation, cost, quality and productivity negatively in a manufacturing context and therefore need to be properly managed. The support towards the operators in manufacturing and manual assembly is generally based on assembly instructions, however, the usage tend to be low which has a negative impact on quality. Therefore, this thesis is focusing on assembly information needs with the goal of improving quality in manual assembly. The thesis has gathered data through interviews with 25 operators, 7 additional engineering roles in the organization, literature studies and a comparison with a newly implemented information system to be able to answer the research questions. Firstly, general findings have been identified such as low and highly variating usage of instructions, the work difficulty is perceived as low, however, still experience quality problems. Secondly, the data analysis shows clear evidence that the information provided and the information need is inconsistent, which consequently has led to that the support towards operators as well as the perceived value of using instructions are too low, leading to quality problems in manufacturing. The assessment of the information needs has been divided into two main parts, current problem areas and focus areas for improvements. The identified problem areas consider: Instruction errors, Updates of instructions, Work training and Feedback and follow-up and are crucial to emphasize to get an effective and efficient way of working and hence support the assembly information system. Moreover, the developed focus areas consider: Assembly information match, Individualized and dynamic information and Structure and visualization and are vital to address in order to improve the assembly information and hence the quality in manual assembly. These focus areas can be seen as the drivers of an improvement of the assembly information, whilst the problem areas can be seen as the enablers of the improvements. The results of this thesis have further been developed through perspectives of standardization to utilize synergetic effects as well of suggested requirement areas for a future assembly information system. This thesis has consequently revealed substantial improvement potentials in terms of assembly information, with the potential to improve quality in manual assembly. The thesis further contributes with a direction for the future based on information needs, which is important for organizations working in this kind of environment to manage product variety, quality, cost and productivity in a business environment characterized by high demands, customization and rapid changes.
Comparison of Sparse Solutions Obtained by Splitting the Sample into Parts Based on External Quality Criteria of Models in the LS-SVM Method

The method of partitioning sample into training and test parts are considered for LS-SVM method with use of methods of optimal experimental design and external criteria quality of models. For partitioning sample into parts are given the corresponding computational schemes. The computational experiment is carried out on a model example. In it, to obtain a sparse solution from the initial sample, the training part of various volumes was extracted. The efficiency of the proposed algorithms was verified in conditions of different noise levels of the useful signal. Comparison of the quality of the obtained solutions was carried out based on the mean square error.
Maximum Efficiency Control of PMSM Drives Considering System Losses Using Gradient Descent Algorithm Based on DC Power Measurement

This paper proposes a novel method of efficiency improvement in a vector controlled permanent magnet synchronous motors (PMSM) through system level maximum efficiency point determination using current angle as a control variable. Loss models for the inverter and the motor fundamental and harmonic losses, which are capable of being solved online using available terminal measurements in the system are initially developed. The loss models and dc-link power measurement are then used to seek the maximum efficiency angle for different operating conditions using a gradient descent optimization algorithm. The developed method is robust against changes in inductances due to saturation and cross saturation with loading conditions as well as temperature effects. The effectiveness of the developed method in improving the system efficiency is verified and compared with conventional maximum torque per ampere method. The proposed strategy has been validated on a laboratory interior PMSM, and the efficiency has been calculated for different speed and torque conditions. The experimental validations confirm the effectiveness of the proposed solution in improving the motor drive system energy efficiency.
Stable Isotope Composition of the Basal Ice from Taylor Glacier, Southern Victoria Land, Antarctica

Summary A tunnel excavated into the margin of Taylor Glacier revealed a basal sequence containing a thick sequence of layers of clean clear ice and debris-rich ice which contained strong deformation features, as well as units of clean bubbly ice. Analysis of the isotopic composition of the basal ice shows a strong linear relationship that plots on a slope of 8, which is usually interpreted as meteoric in origin. However, the physical appearance of the laminated ice is inconsistent with a meteoric-origin interpretation and has the outward appearance of ice usually inferred as the product of basal melt-refreeze processes like regelation. We consider this apparent tension between physical appearance and isotopic composition of the Taylor Glacier basal ice to be a limitation of the stable isotope approach, and that the technique employed here is unable to diagnose small-scale processes like regelation.