Miracle-dz/UniFAR-FTUs huggingface dataset:
Incidence of multidrug resistant Vibrio parahaemolyticus isolated from Ponnani, South India

Background and Objectives The prevalence of Vibrio parahaemolyticus has been reported from Ponnani earlier, however incidence of multidrug resistant strains have been encountered recently in clinical laboratories. The source for such strains and their presence in this major fish landing centre has been investigated. Materials and Methods Antibiotic sensitivity tests on isolates of V. parahaemolyticus isolated from three different substrates were conducted following disc diffusion method. Results Populations of V. parahaemolyticus (cfu/ml) were relatively high in sediment samples (7.67 ± 2.08), compared to shrimp (5.33 ±1.53) and water samples (3.67 ± 1.15). V. parahaemolyticus isolated from water showed relatively higher antibiotic resistance pattern compared to other two groups. The highest incidence of antibiotic resistance was recorded against cephalothin and nitrofurantonine; the lowest was against tobramycin, piperacillin and amikacin. Maximum multiple drug resistant (MDR) strains were encountered from water samples followed by shrimps. Conclusion Results emerging from the present study clearly showed that Ponnani has a fairly good population of antibiotic resistant strains of V. parahaemolyticus. The present study provides an insight on the microbial population of V. parahaemolyticus in Ponnani harbour and warrants the need to develop control measures to reduce incidences of post-harvest contamination of seafood.
Cartesian coordinate control for redundant modular robots

The paper focuses on the kinematic control of redundant modular robots for trajectory tracing. Based on the geometric numerical inverse kinematic algorithm developed for modular robots, a new online control method is presented. In this method, the inverse kinematic solution can be optimized through constructing a weighted matrix. Following this approach, some fundamental interpolation algorithms are proposed for Cartesian space (task space) control of redundant modular robots. The effectiveness of the proposed algorithms has been experimentally demonstrated by a 7-DOF serial modular robot that performs a pick-and-place task with the avoidance of joint angle limits.
Using sound to enhance users' experiences of mobile applications

The latest smartphones with GPS, electronic compass, directional audio, touch screens etc. hold potentials for location based services that are easier to use compared to traditional tools. Rather than interpreting maps, users may focus on their activities and the environment around them. Interfaces may be designed that let users search for information by simply pointing in a direction. Database queries can be created from GPS location and compass direction data. Users can get guidance to locations through pointing gestures, spatial sound and simple graphics. This article describes two studies testing prototypic applications with multimodal user interfaces built on spatial audio, graphics and text. Tests show that users appreciated the applications for their ease of use, for being fun and effective to use and for allowing users to interact directly with the environment rather than with abstractions of the same. The multimodal user interfaces contributed significantly to the overall user experience.
Estimating Dynamic Panel Data Models with Measurement Errors with an Application to School Evaluation based on Student Test Scores

A key di‐culty in drawing inference of school efiect from student test score gains is the fact that test scores are noisy measurements of students’ academic achievements. In this paper we examine competing inferential methods of dynamic panel data models using noisy data. In particular, we consider a score-level model where the score of the current period depends on the score of the previous period. We compare Monte Carlo simulation results of estimators of this model and estimates using the student test score data of Missouri.
Application of document spelling checker for Bahasa Indonesia

The needs of document spelling checker of Bahasa Indonesia is highly required. Unfortunately, there is no available application of document spelling checker for Bahasa Indonesia. The existing researches on Indonesian spelling checker have not developed into a complete document spelling checker. Here in this research, we compare several methods employed for Indonesian spelling checker especially in the word error detection and analyzed best methods employed in the building of Indonesian document spelling checker application. The main idea is to employ a complete word list as the reference. The Indonesian document spelling checker consists of 5 main components, namely document preprocess, word error detection, word error correction, word candidate ranking, and user feedback. The document preprocess is to process the document into a list of unique word which will be analyzed further in the spelling checker. In the word error detection, a binary search and hashing are used to do the searching faster. In the word error correction, the forward reverse and a similarity measure score are employed. In the candidate ranking, HMM is used to select the best correct word candidate. Using 13,000 words as the lexicon resource and 10 documents as the tested documents, the experimental results achieved 93.7% accuracy. The errors are caused by the word absence in the lexicon resource and the special repetition word form.
A Big Data Science Experiment -- Identity Deception Detection

Identity Deception Detection is a problem on social media platforms today. Not only is there challenges towards determining the authenticity of people, but also with analyzing the data that forms part of the communications. These data are of heterogeneous type and include photos, videos and sound. Furthermore, most social media platforms are operating in an uncontrolled environment. Any person can contribute content and take part. Even though age restrictions do exist there are no enforcement of these laws and honesty of the public is expected. This is dangerous for minors specifically as they are either unaware of the dangers or not mature enough to be responsible for their actions online. Online predators are aware of this fact and targeting this group specifically. This paper presents work-in-progress towards developing an intelligent Identity Deception Indicator (IDI). It is envisaged that this work could eventually assists authorities in doing large-scale observation on publicly available social media platforms, such as Twitter. Of particular interest are those personas whose behavior and online content does not fit with the age group they are conversing with.
Grid-based Network Architecture for Distributed Computation in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are used to perform distributed sensing in various fields, such as health, military, home etc. In WSNs, sensor nodes should communicate among themselves and do distributed computation over the sensed values to identify the occurrence of an event. This paper assumes the no memory computation model for sensor nodes, i.e. the sensor nodes only have two registers. This paper presents an optimal architecture for the distributed computation in WSN and also claims that this architecture is the optimal for the described computation model.
Creep Predicting Model in Masonry Structure Utilizing Dynamic Neural Network

Problem statement: When the loads are applied to a brickwork structure, visco-elastic behavior upon their stress-strain relationships is exhibited, where the response can be classified into two separate parts: an instantaneous elastic strains and time-dependent creep strains. The creep strain represents the non- instantaneous strain that happens with time when the stress is sustained. Through the previous century, along with the alter in brickwork construction, A chain of creep tests on brickwork has shown that creep in brickwork be able to result in deformation that rise gradually with the way of time. Brickwork has considerable creep strain that is complicated to predict because of its reliance on several unrestrained parameters (e.g., relative humidity, time of load application, stress level). Dependable and precise prediction models for the long term, time-dependent creep deformation of brickwork structures are required. Artificial Neural Network (ANN) models have been determined useful and efficient especially in such problems for which the characteristics of the processes are difficult to describe using numerical models. Approach: This study introduces a creep prediction model based Focused Time-Delay Neural Network (FTDNN) which could detect and consider within its architecture the time dependency which is major factor in creep deformation in brickwork structure. Results: Performance of the proposed FTDNN model was examined with experimental creep data from brickwork assemblages collected over the last 15 years. Results showed that the FTDNN model has a relatively small prediction error compared to the other models with the error less than 15%. Conclusion: The results showed that the FTDNN model outperformed the existing ANN models and significantly enhance the accuracy of creep prediction.
Discovery of Spectral Variability of Markarian 421 at TeV Energies

The detection of spectral variability of the γ-ray blazar Mrk 421 at TeV energies is reported. Observations with the Whipple Observatory 10 m γ-ray telescope taken in 2000/2001 revealed exceptionally strong and long-lasting flaring activity. Flaring levels of 0.4-13 times that of the Crab Nebula flux provided sufficient statistics for a detailed study of the energy spectrum between 380 GeV and 8.2 TeV as a function of the flux level. These spectra are well described by a power law with an exponential cutoff: dN/dE ∝ E-αe m-2 s-1 TeV-1. There is no evidence for variation in the cutoff energy with flux, and all spectra are consistent with an average value for the cutoff energy of 4.3 TeV. The spectral index varies between 1.89 ± 0.04stat ± 0.05syst in a high flux state and 2.72 ± 0.11stat ± 0.05syst in a low state. The correlation between spectral index and flux is tight when averaging over the total 2000/2001 data set. Spectral measurements of Mrk 421 from previous years (1995/1996 and 1999) by the Whipple collaboration are consistent with this flux-spectral index correlation, which suggests that this may be a constant or a long-term property of the source. If a similar flux-spectral index correlation were found for other γ-ray blazars, this universal property could help disentangle the intrinsic emission mechanism from external absorption effects.
The asymptotic rank of metric spaces

In this article we define and study a notion of asymptotic rank for metric spaces and show in our main theorem that for a large class of spaces, the asymptotic rank is characterized by the growth of the higher isoperimetric filling functions. For a proper, cocompact, simply connected geodesic metric space of non-positive curvature in the sense of Alexandrov the asymptotic rank equals its Euclidean rank. Mathematics Subject Classification (2010). 49Q15.
Finger Gesture Recognition Using Microphone Arrays

Although gestures and movement are a natural, everyday occurrence, it remains to be a complex event to interpret by modern day devices. Research has taken a step forward towards solving this problem by discovering alternative methods in an attempt to capture complex gestures. Usually, we interact with our devices by either physical touch or even voice. As these devices become more sophisticated and smaller in size, we should consider whether we could have these devices potentially do more than just simply react to our touch or voice. In this paper, we consider the possibility of interactive and subtle gesture recognition. Specifically, we consider the ability to detect the gestures by emitting ultrasonic waves through the air using microphones and speakers from a typical mobile device. Through movement, these waves are altered, providing ways to interpret gestures. In this work, we particularly focus on finger tapping gestures. We ultimately envision a device that provides the user with the ability to wear it on their wrist, such as a watch. As the user wears the device, it would emit an ultrasonic wave (when prompted), which is then interpreted by it’s own microphones. This challenge is extended further in the case of finger gestures, where the only possible gesture movements that take place are in a close proximity to each other. In this work, we describe finger gesture recognition using a microphone array. First we try to use the reflection of sound waves by implementing an acoustic pulse radar. After understanding we cannot obtain a fine resolution to detect a subtle gesture, we implement a logistic regression classifier using the features from Doppler shift for each microphone. After testing the classifier on different data sets, we conclude that the classifier can be trained successfully with simply a small number of samples for each person. We also find that a learned classifier from one person, does not generalize well to a different person.
Does Shape Discrimination by the Mouth Activate the Parietal and Occipital Lobes? – Near-Infrared Spectroscopy Study

A cross-modal association between somatosensory tactile sensation and parietal and occipital activities during Braille reading was initially discovered in tests with blind subjects, with sighted and blindfolded healthy subjects used as controls. However, the neural background of oral stereognosis remains unclear. In the present study, we investigated whether the parietal and occipital cortices are activated during shape discrimination by the mouth using functional near-infrared spectroscopy (fNIRS). Following presentation of the test piece shape, a sham discrimination trial without the test pieces induced posterior parietal lobe (BA7), extrastriate cortex (BA18, BA19), and striate cortex (BA17) activation as compared with the rest session, while shape discrimination of the test pieces markedly activated those areas as compared with the rest session. Furthermore, shape discrimination of the test pieces specifically activated the posterior parietal cortex (precuneus/BA7), extrastriate cortex (BA18, 19), and striate cortex (BA17), as compared with sham sessions without a test piece. We concluded that oral tactile sensation is recognized through tactile/visual cross-modal substrates in the parietal and occipital cortices during shape discrimination by the mouth.
Structure and folding of the Tetrahymena telomerase RNA pseudoknot

Telomerase maintains telomere length at the ends of linear chromosomes using an integral telomerase RNA (TER) and telomerase reverse transcriptase (TERT). An essential part of TER is the template/pseudoknot domain (t/PK) which includes the template, for adding telomeric repeats, template boundary element (TBE), and pseudoknot, enclosed in a circle by stem 1. The Tetrahymena telomerase holoenzyme catalytic core (p65-TER-TERT) was recently modeled in our 9 Å resolution cryo-electron microscopy map by fitting protein and TER domains, including a solution NMR structure of the Tetrahymena pseudoknot. Here, we describe in detail the structure and folding of the isolated pseudoknot, which forms a compact structure with major groove U•A-U and novel C•G-A+ base triples. Base substitutions that disrupt the base triples reduce telomerase activity in vitro. NMR studies also reveal that the pseudoknot does not form in the context of full-length TER in the absence of TERT, due to formation of a competing structure that sequesters pseudoknot residues. The residues around the TBE remain unpaired, potentially providing access by TERT to this high affinity binding site during an early step in TERT-TER assembly. A model for the assembly pathway of the catalytic core is proposed.
Effect of Biofield Energy Treatment on Chlorophyll Content, Pathological Study, and Molecular Analysis of Cashew Plant ( Anacardium occidentale L.)

In the world scenario, India occupies a premier position contributing to about 43 per cent production of the cashew nut (Anacardium occidentale L.) along with export and processing. The aim is to study the impact of biofield energy treatment on selected farms for cashew farming. The control and biofield treated farms were divided as control and treated farms, and Mr. Trivedi provided the biofield energy treatment to the treated farms. Further, the plants and fruits were analyzed for overall growth of plants, chlorophyll content, productivity, pathological study, and shelf life using UN specifications for International Trade, biophoton emission study, and DNA fingerprinting using RAPD method. No chemicals, fertilizers, were used on the treated plot, although regular practices were followed on control farms such as fertilizers, pesticides and fungicides due to the high incidence of disease and the requirement of nutritional supplements in the region. The analysis showed that biofield treated farm plants have thicker and stronger branches with more secondary and tertiary branches, flowering pattern, and canopy of plants was improved than trees of the same variety along with height of the plants, as compared with the control. The results showed that chlorophyll a and b content in biofield treated lands plants were increased by approximately 30% and 93% respectively, while total chlorophyll content by 45% as compared with the control. The pathological examination showed the presence of fungi namely Colletotrichum gloeosporioides and Botryodiplodia theobromae in control, which were absent in treated plants. Biophoton study suggested that the cashew fruits were bigger in size with high density, strength, and vitality as compared with the control. The shelf life analysis reflected that the biofield treated cashews showed sweet taste, and can be stored for longer duration due to less moisture, and altered minerals content, such as high iodine, and low p-anisidine level. RAPD analysis showed a high level of polymorphism among control and treated samples, while level of true polymorphism among V4 variety of cashew was ranges from 0 to 100%, and in V7 variety, it ranged from 25 to 91% using different set of RAPD primers. Overall, study results suggest that Mr. Trivedi’s biofield energy treatment on land planted with cashew could be an alternative approach to improve the overall growth of plant, and fruit yield.
An effective self-adaptive mean filter for mixed noise

The image is usually corrupted by Gauss noise and impulse noise simultaneously, and its quality will be reduced. Thus filtering image is important in image processing. The traditional mean filter cannot remove impulse noise effectively while preserve the details of image well. And the median filter cannot remove Gauss noise effectively. In this paper, we propose the self-adaptive mean filter to remove mixed noise of Gauss noise and impulse noise. Firstly, dividing pixels of image into good pixels and corrupted pixels based on whether there are noises in their small neighborhoods. And the greyscale value of good pixels are output directly. Secondly, for corrupted pixels, removing Gauss noises and impulse noises respectively based on characteristics of different noise. The results demonstrate that the self-adaptive mean filter can eliminate mixed noise of different density better and preserve the details of image better comparing with the mean filter or the median filter for mixed noise.
Directional local region-scalable active contour using expandable kernel

This paper extracts another benefit of local region-scalable active contour using expandable kernel (LREK) [1]. We modify it to posses a directional property so that it is capable in detecting objects of desirable edge's type. Local region-scalable force is determined by pixel's intensity profile within expandable kernels centered on the contour. While magnitude of intensity difference is used in adaptive local statistics of expandable kernel, sign of the difference is a directional information in controlling the forces to attract the contour only into a particular edge's type object. By setting a directional parameter, an initial contour placement results in two different segmented outcomes. Formulated via level set, our model is topologically flexible. Local region-scalable information enables our model to converge quickly into desired objects with noises, intensity inhomogeneity, and heterogeneous textures. Moreover, the adaptive local statistics allows in tracing concave boundary with a large capture range.
Peruvian Privatization: Impacts on Firm Performance

In the nearly ten years since Peru privatized major State Owned Enterprises (SOEs), the overall impact of the process is not yet clear. This paper analyzes the impact of privatization through a detailed statistical and econometric analysis of first difference (the difference between pre- and post-privatization performance), and second difference (change in performance of privatized firms relative to the change in performance of SOEs) of several indicators on profitability, operating efficiency, employment, leverage and convergence. The results, which showed that privately owned firms are more efficient and more profitable than otherwise comparable state owned firms, were consistent with previous literature. In the case of the most competitive sector, the financial system, the newly privatized banks converged towards the leading private banks over time. While the impact of privatization on employment is negative in the short-run, there are more positive impacts in the long term, especially since SOEs traditionally hire employees for political rather than technical reasons. This paper demonstrates that, as the result of privatization, there is a significant increase in indirect employment through services and significant growth of total employment—both direct and indirect.
Visual analytics for the interpretation of fluency tests during Alzheimer evaluation

A possible way to evaluate the progress of Alzheimer disease is to conduct the Isaac set test [13, 14]. In this activity, patients are asked to cite the largest possible number of city names within a minute. Since the city names are handwritten very quickly by a medical practitioner some cities are abbreviated or poorly written. In order to analyze such data, medical practitioners need to digitize the notes first and clean the dataset. Because these tasks are intricate and error prone we propose a novel set of tools, involving interactive visualization techniques, to help medical practitioners in the digitization and data-cleaning process. This system will be tested as part of an ongoing longitudinal study involving 9500 patients.