Miracle-dz/UniFAR-FTUs huggingface dataset:
Silver and Magnetic Iron Oxide Nanoparticles-Assisted PCR for the Phytopathogenic Bacteria Ralstonia solanacearum

Nanotechnology became an integrated science in different fields. Integration between nanoscience and molecular diagnosis could enhance the early diagnosis of different pathogens. Enhancement of different molecular techniques by using nanomaterials increases the specificity, sensitivity and application of these techniques in biology. Polymerase chain reaction (PCR) is considered as one of the main basic molecular techniques that could be enhanced by using nanomaterials. Silver (Ag) and magnetic iron oxide (Fe2O3) nanoparticles were chemically synthesized and characterized by using transmission electron microscope (TEM) according to standard protocol. The sizes of Ag and magnetic Fe2O3 nanoparticles were ∼15-20 and ~12-23 nm diameters respectively. DNA template of Ralstonia solanacearum was extracted by using Ag and magnetic Fe2O3 nanoparticles separately and in mixture of both nanomaterials in addition to the control. Extraction of DNA template by using combined nanomaterials increased the DNA yield followed by significant augmentation of the PCR efficacy for small concentration of bacterial DNA template. Inspections of the mechanism of such PCR augmentation suggested an indication of quick transfer of heat in the presence of Ag and magnetic Fe2O3 nanoparticles. Silver and magnetic Fe2O3 nanoparticles-supported PCR could be applicable for reducing the total PCR cycles and enhancing the augmentation of DNA amplicons from a diversity of samples, as well as GC-rich patterns (such as the bacterial genome of R. solanacearum) that are frequently observed to yield disappointing results.
More Than Blips on the Radar: Exploring Immersive Visualization for Maritime Decision Making

Decision-making in maritime environments often requires large amounts of data from numerous different sources including local ship-mounted sensors, collaborating vessels in the region and ground stations. On-board data specialists use computer-aided methods to interpret these data and to provide pertinent information for decision makers. Immersive Analytics can help specialists to explore the data more efficiently, however current interaction techniques limit both exploration and adoption. This work discusses current research goals on interaction methodologies for mixed reality immersive visualization for collaborative work. We have created a simple prototype that allows users to collaborate in an immersive environment using multiple HoloLens and a projection mapped tabletop display. In its current form, users can join the augmented reality session (with position and orientation tracking) and visually explore the data.
Adaptive VR-based rehabilitation to prevent deterioration in adults with cerebral palsy

Cerebral palsy (CP) is a disabling life-long condition progressively impeding a patient’s independence. Although incident rates are high, a clear understanding of the disease is missing. CP is characterized by several motor disorders and sensory or perceptive comorbidities. This multifaceted nature complicates proper diagnosis and hampers the search for possible treatments. During adolescence and adulthood, individuals with CP experience a drastic deterioration in gross motor control, independence, and quality of life. There is poor evidence that physical therapy promotes the retention of function through aging, and no clinical studies exist that explore the potential of VR-based training to prevent deterioration. In this pilot randomized controlled trial, we expose 14 adults with CP to the Rehabilitation Gaming System (RGS) and examine its usability, effectiveness, and acceptability. Our results show that the RGS difficulty adaptation algorithm automatically matches the patients’ impairment level as captured by clinical scales (Barthel and Box & Blocks). The clinical effectiveness and acceptability of the RGS and conventional therapy were comparable. We conclude that VR-based physical therapy as an adjunct to usual treatment may be a promising approach for the prevention of deterioration in adolescents and adults with CP.
Extracting Social Network from Literary Prose

This thesis develops an approach to extract social networks from literary prose, namely, Jane Austen’s published novels from eighteenthand nineteenthcentury. Dialogue interaction plays a key role while we derive the networks, thus our technique relies upon our ability to determine when two characters are in conversation. Our process involves encoding plain literary text into the Text Encoding Initiative’s (TEI) XML format, character name identification, conversation and co-occurrence detection, and social network construction. Previous work in social network construction for literature have focused on drama, specifically manually TEIencoded Shakespearean plays in which character interactions are much easier to track in due to their dialogue-driven narrative structure. In contrast, prose is structured quite differently; character speeches are not very clearly formatted, making it more difficult to assign specific dialogue to each character. We implement two different parsing strategies based on context size (chapter scope and paragraph scope) to detect character interactions. To check the accuracy of our methods, we conduct one evaluation that is based on network statistics and another evaluation that involves measuring similarity (edit distance) between the networks constructed from manually encoded novels versus our constructed graphs. Our findings suggest that the choice of context size is non-trivial and can have a substantial influence on the resulting networks. In general, the paragraph level interaction approach seemed to be more accurate.
Urine versus Pre-mix (Sugar: Salt): Baits for Stingless Bees (Hymenoptera: Meliponini)

Stingless bees are dispersed throughout Malaysia and form an important group of pollinators in agriculture and natural ecosystems. A study was conducted at Lojing Highland in Kelantan, Malaysia on the preference of stingless bees towards pre-mix bait [sugar and salt (1:2) (sugar: water:v:v)] with 2.5g NaCl added per 500 ml of solution] and urine bait for two consecutive days. A total of 285 stingless bees of 15 species were sampled for this purpose. Overall, stingless bees showed no preference for either bait, but a closer examination showed species-level preferences. Five species preferred urine bait over pre-mix bait, and another eight preferred pre-mix bait over urine bait. No significant differences were found on stingless bees preferences towards pre-mix bait and urine baits (p>0.05). Five stingless bee species (Lisotrigona scintillans, Pariotrigona pendleburyi, Lepidotrigona ventralis, Tetrigona apicalis, and Tetragonula collina) were found to be frequently attracted to the urine bait compared with pre-mix bait. Meanwhile, eight stingless bee species attracted to pre-mix bait compared with urine bait. This study shows that stingless bees’ preference for pre-mix or urine baits depends on species.
An Experimental Analysis Of The Applications Of Datamiing Methods On Bigdata

Data mining is a procedure of separating covered up, obscure, however possibly valuable data from gigantic data. Huge Data impactsly affects logical disclosures and worth creation. Data mining (DM) with Big Data has been broadly utilized in the lifecycle of electronic items that range from the structure and generation stages to the administration organize. A far reaching examination of DM with Big Data and a survey of its application in the phases of its lifecycle won't just profit scientists to create solid research. As of late huge data have turned into a trendy expression, which constrained the analysts to extend the current data mining methods to adapt to the advanced idea of data and to grow new scientific procedures. In this paper, we build up an exact assessment technique dependent on the standard of Design of Experiment. We apply this technique to assess data mining instruments and AI calculations towards structure huge data examination for media transmission checking data. Two contextual investigations are directed to give bits of knowledge of relations between the necessities of data examination and the decision of an instrument or calculation with regards to data investigation work processes.
DENOISING OF 3D POINT CLOUDS

Abstract. A method to remove random errors from 3D point clouds is proposed. It is based on the estimation of a local geometric descriptor of each point. For mobile mapping LiDAR and airborne LiDAR, a combined standard mesurement uncertainty of the LiDAR system may supplement a geometric approach. Our method can be applied to any point cloud, acquired by a fixed, a mobile or an airborne LiDAR system. We present the principle of the method and some results from various LiDAR system mounted on UAVs. A comparison of a low-cost LiDAR system and a high-grade LiDAR system is performed on the same area, showing the benefits of applying our denoising algorithm to UAV LiDAR data. We also present the impact of denoising as a pre-processing tool for ground classification applications. Finaly, we also show some application of our denoising algorithm to dense point clouds produced by a photogrammetry software.
Physiological Adaptability and Parametric Versatility in a Simple Genetic Circuit

The intimate relationship between the environment and cellular growth rate has remained a major topic of inquiry in bacterial physiology for over a century. Now, as it becomes possible to understand how the growth rate dictates the wholesale reorganization of the intracellular molecular composition, we can interrogate the biophysical principles underlying this adaptive response. Regulation of gene expression drives this adaptation, with changes in growth rate tied to the activation or repression of genes covering enormous swaths of the genome. Here, we dissect how physiological perturbations alter the expression of a circuit which has been extensively characterized in a single physiological state. Given a complete thermodynamic model, we map changes in physiology directly to the biophysical parameters which define the expression. Controlling the growth rate via modulating the available carbon source or growth temperature, we measure the level of gene expression from a LacI-regulated promoter where the LacI copy number is directly measured in each condition, permitting parameter-free prediction of the expression level. The transcriptional output of this circuit is remarkably robust, with expression of the repressor being largely insensitive to the growth rate. The predicted gene expression quantitatively captures the observations under different carbon conditions, indicating that the bio-physical parameters are indifferent to the physiology. Interestingly, temperature controls the expression level in ways that are inconsistent with the prediction, revealing temperature-dependent effects that challenge current models. This work exposes the strengths and weaknesses of thermodynamic models in fluctuating environments, posing novel challenges and utility in studying physiological adaptation. Significance Cells adapt to changing environmental conditions by repressing or activating gene expression from enormous fractions of their genome, drastically changing the molecular composition of the cell. This requires the concerted adaptation of transcription factors to the environmental signals, leading to binding or releasing of their cognate sequences. Here, we dissect a well characterized genetic circuit in a number of physiological states, make predictions of the response, and measure how the copy number of a regulator and its gene target are affected. We find the parameters defining the regulators behavior are remarkably robust to changes in the nutrient availability, but are susceptible to temperature changes. We quantitatively explore these two effects and discuss how they challenge current models of transcriptional regulation.
Development of digital interactive math comics (DIMaC) for senior high school students in general mathematics

Abstract Supporting the 21st-century learners’ instructional needs is a trend of today’s educational system. This educational design research aimed to develop a Digital Interactive Math Comics (DIMaC) as an instructional material envisioned to meet these learners’ needs to a better understanding of Mathematics concepts. This employed the ADDIE framework for instructional material development design. There were 425 randomly chosen students who took the validated and acceptable with 0.7888 Cronbach’s alpha researcher-made General Mathematics Competency Test. This was done to identify the least learned skills and be the basis for design and development. The initial storyline with the Mathematics contents integrated were validated by the set of experts before the electronic illustrations and coding took place. The initial outputs of the DIMaC were revalidated for comments and suggestions before distribution for classroom use. These experts also evaluated the final version of DIMaC as very acceptable. The DIMaC was then implemented in a classroom and found to have high usability as rated by the students. Also, the app draws positive feedback for classroom use because of its interesting nature and uniqueness. Thus, this study adds to the body of literature on helpful instructional materials for utilization to these tech-savvy learners.
Synchronization of Synchronous Reluctance Motors Using the Discrete Sliding Mode Control Technique

The synchronous reluctance motor (SynRM) drive system is known to exhibit chaotic behavior under specified conditions. In this paper, the discrete-time sliding mode control (DSMC) technique is used to synchronize two SynRMs starting from different sets of initial conditions. The mixed variable speed reaching law is adopted in the design of the controller scheme. The parameters of the designed control scheme are tuned using a genetic algorithm (GA). Simulation results are presented to demonstrate the effectiveness of the proposed controller. In addition, the performance of the proposed control scheme is studied through simulations when bounded disturbances and mismatches between the parameters of the systems and those of the control scheme exist. The simulation results show that the designed control scheme is robust to bounded external disturbances and to mismatches in the parameters of the systems.
Urban Flood Scaling Using Hydrologic and Hydraulic Models with Inception for Early Warning

Urban floods are generally characterized by surge in runoff volumes resulting in high flow peaks and water depths incurring huge socioeconomic losses. Hydrologic and hydraulic simulation tools integrated with ground survey inputs can be effectively used to simulate the movement of flood waters in intricate urban environments. Integration of hydrological–hydraulic flood models supported by geospatial tools and hydro-meteorological analysis is one effective measure to comprehend urban flooding. Numerical Weather Prediction (NWP) models as WRF aided aided by Nowcasting DWR observations is one resourceful tool for urban flash flood forecasting. The NWP forecasted precipitation data is conglomerated to a distributed hydrological model to derive flood hydrographs. The theme of the study is to establish flood runoff thresholds in one of the most flood-prone urban region of India – Guwahati city, by simulating the spatial flooding extents, developing flood runoff thresholds and to scale the flood events. Database build up for actual flooding events, ground reconciliation using ETS-RTK survey, setting up of Base Flood Elevation (BFE) points for hydraulic model integration was done. The resulting hybrid DEM (1m resolution) was adopted for building the spatially-distributed hydrological model in HEC-HMS. Model runs were carried out to derive flood runoff hydrographs and peak discharges using time series NWP–WRF and AWS data. Drainage active areas, building footprints and blockages in storm drains were laid over the high resolution 1m bathymetric grid in hydraulic MIKE FLOOD model. Flood inundation simulation using runoff hydrographs were carried out under source/sink pairs. Schematization of the simulated flood inundation layers using threshold scales of flood discharges was used to develop a scaling of the urban flooding in Guwahati, with early warning inception.
Effect of Plectranthus amboinicus leaf extract on the quality attributes of microencapsulated fish oil fortified soup powder

The effect of Plectranthus amboinicus leaf extract (PAE) (phenolic content of 2559.56 mg gallic acid equivalents/L) addition in a microencapsulated fish oil fortified soup powder was evaluated in the present study. Fortification of PAE significantly improved the color, rehydration and water activity of the soup powder. The oxidative indices unveiled the role of PEA in protecting the MFO fortified soup powder from oxidative deterioration during the storage period. No faecal coliforms, yeast and mould growth was observed in MFO and PAE fortified soup powder whereas mould growth was there in the control samples. The fortified soup powder has scored high in terms of aroma, taste, consistency and overall acceptability proving its sensory acceptance. The significant findings of the storage study clearly depicted the antioxidant, antibacterial, antifungal as well as flavour enhancing potential of PAE and hence it can be recommended as a potent natural preservative for fish oil incorporated food systems.
Digital image watermarking using fast parametric transforms

This paper proposes a novel method for digital image watermarking, in which watermarks are embedded in the domain of fast parametric transforms based on known spread spectrum approaches. Fast parametric transforms have the ability to adapt the forms of base vectors, which enables automatic selection of the domain of watermarking in relation to the pair: a marked image – a watermarking attack. The process of adapting the forms of fast parametric transforms is carried out with aid of the classical genetic algorithm with the ﬁtting function based on the known measure of separability of watermarks. The eﬀectiveness of the proposed method has been veriﬁed experimentally on the basis of the images of two classes, i.e. natural images and technical diagrams. The results taking into account both the eﬃciency of watermark embedding and the generated distortions in the marked images are summarized in tables and accompanied by an appropriate commentary.
Impact of Corporate Governance on Earnings Management: Large Sample Evidence from India

The central point of this examination is to research the effect of corporate governance on earning management practices in India. Its results, if proved significant, can thereon be applied to curb earnings management. We utilized random-effect point estimates on 1613 non-Finance organizations working in the Indian subcontinent. The data pans from 2004 till 2018. Corporate governance has been evaluated on the basis of four of its divergent practices (board size, CEO? chair duality, managerial ownership, and audit committee independence) while discretionary accruals have been utilized as an intermediary for estimating malpractices in the income. This has been accomplished by employing the modified Jones model (Dechow et al., 1995) to obtain the results. The empirical findings are in accordance with the concept of corporate governance. CEO-chair duality is significantly connected with practices of earnings management and is thus, noteworthy. However, one of the corporate administration factors, board size, is found irrelevantly identified with earnings manipulation. The examination enhances the current writings on the subject matter; that there is a negative relationship with the two major areas of the study, namely, corporate governance and earnings manipulation. The investigation accords explicitly by confirming that in emerging nations, corporate administration must have a negative impact on the issue of earnings manipulation. The importance of the research is enhanced by the prevalence of the, so called, ? interest war? among the minority and controlling shareholder(s) than between the executives and proprietors, in developing countries like India.
Factors Influencing Successful Fishing of Tuna Free-Swimming Schools in the Equatorial Western Pacific Ocean

1Shanghai Ocean University, College of Marine Sciences, Shanghai 201306, P. R. China. 2Collaborative Innovation Center for Oceanic Fisheries, Shanghai 201306, P. R. China. 3National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, P. R. China. 4Shanghai Ocean University, Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, P. R. China. 5P.O. Box 21691, Juneau, Alaska 99802, United States of America.
Introduction to the Special Issue Leisure Research to Enhance Social Justice

Several streams of leisure research are directed at furthering an agenda for social justice. These lines of inquiry are motivated by the need to end various kinds of oppression related to one’s gender, race, ethnicity, sexual identity, ability, and socio-economic status. Rather than social justice, this special issue is focused on research frameworks that further social justice. Three inter-related research criteria are applied: (1) identification of a value orientation and vision for social justice, (2) development of a social or cultural framework to enhance social justice, and (3) connection to social and political action to move communities in the direction of a more socially just set of relations. These three research criteria are applied to three approaches to research: descriptive, explanatory, and transformative. The purpose of this special issue is to build capacity of leisure research to enhance social justice.
Performance and Heat Release Rate Comparison in a Diesel Engine fueled with Sunflower Methyl Esters/Diesel Fuel Blend

Biodiesel fuels are among the leading renewable alternative fuels. And, using biodiesel fuels is available and easy to implement on diesel engines. Biodiesel fuels, methyl/ethyl esters of various oils extracted from vegetables or animals, are being used by many researchers on various types of engines and they were tested at various conditions. Since chemical properties very close to diesel fuel, similar test results for nominal engine performance data with diesel can be obtained by using biodiesel fuels on engines. In this study, effect of sunflower oil methyl esters on engine performance, heat release rate and indicated engine parameters are investigated experimentally on a single cylinder, DI Diesel engine. Tests are performed with diesel fuel and B50 blend fuel, consisting of 50% diesel and 50% biodiesel fuels, at full load condition and at different speeds. Engine brake torque, brake power, brake specific fuel consumption, brake thermal efficiency, heat release rate, and indicated engine parameters are calculated from the test data, and the results obtained by using diesel fuel and B50 blend fuel are compared. Although some worsening on performance data and heat release rate on B50 side, results are very close to each other.