Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on Heavy Metal Resistant Fecal Coliforms Isolated From Industrial, Urban Uastewater in Arak, Iran

In this essay, the heavy metal resistance patterns of bacterial strains isolated from industrial wastewater, domestic wastewater and various parts of the wastewater treatment system of Arak city have been studied. 28 intestinal bacterial strains were screened and identified as Klebsiella, Escherichia coli, Citrobacter and Enterobacter species biochemical methods. The minimum inhibitory concentration (MIC) against the various heavy metals including cadmium chloride, nickel sulfate, mercuric chloride, potassium chromate and potassium tellurite were determined using the agar dilution method and some antibiotics by disk method. In this study, for first time, we have found high MIC for Klebsiella sp. , 22 mM (4032 μg/ml) for cadmium, 20 mM (3884 μg/ml) for chromium, 20 mM (6157 μg/ml) for telluride, 10 mM (2628 μg/ml) for nickel and 1mM (271.5 μg/ml) for mercury. Furthermore, the bacterial strain Escherichia coli DH5α was transformed with plasmid isolated from Cd2+ resistant Klebsiella sp. The same size of the plasmid was isolated from transformed E.coli DH5α and separated on 0.8% agarose gel electrophoresis. The curing was carried out by exposing cell culture overnight to Sodium Dodechyl Sulphate, which resulted in losing their resistance to cadmium, and therefore, the ability of Klebsiella sp. resistant to cadmium is plasmid mediated
Moving Least Squares Boundaries for SPH Fluids

The paper shows that the SPH boundary handling of Akinci et al. [AIA∗12] suffers from perceivable issues in planar regions due to deviations in the computed boundary normals and due to erroneous oscillations in the distance computation of fluid particles to the boundary. In order to resolve these issues, we propose a novel boundary handling that combines the SPH concept with Moving Least Squares. The proposed technique significantly improves the distance and normal computations in planar boundary regions, while its computational complexity is similar to Akinci’s approach. We embed the proposed boundary handling into Implicit Incompressible SPH in a hybrid setting where it is applied at planar boundaries, while Akinci’s technique is still being used for boundaries with complex shapes. Various benefits of the improved boundary handling are illustrated, in particular a reduced particle leakage and a reduced artificial boundary friction.
Genetic alterations and PIK3CA gene mutations and amplifications analysis in cervical cancer by racial groups in the United States

Introduction: A number of studies indicated racial differences in cervical cancer outcomes and several factors are associated with it such as stage, comorbidities, treatment pattern, and socioeconomic status. However, the associations of tumor genomic patterns such as phosphatidylinositol 3-kinase catalytic subunit alpha (PIK3CA) gene mutations and amplifications with cervical cancer racial disparities are largely unexplored. Objectives: Therefore, the present investigation aimed to identify genetic alterations (mutations and copy number variations) in cervical cancer and determine whether the PIK3CA gene mutations and amplifications in cervical cancer differ across racial/ethnic groups in the United States. Methods: This study made use of The Cancer Genome Atlas (TCGA) database. TCGA database is a publicly available database that was created by a joint effort between the National Cancer Institute and the National Human Genome Research Institute. The two-tailed Fisher’s exact test was used to test for associations between the categorical variables, race, and PIK3CA gene mutation as well as PIK3CA gene amplification using the “Fisher test” function in R. Results: There were 309 cervical cancer samples, and of these, 194 samples had gene mutations and 295 samples had copy number alteration data. The top five mutated genes in TCGA dataset were PIK3CA, MUC4, KMT2C, SYNE1, and KMT2D. The top five amplified genes in TCGA dataset were MECOM, TP63, PRKCI, PIK3CA, and TRFC. The PIK3CA gene had the highest number of mutations with 53 mutation counts. The mutation rates were 62.5%, 31.3%, 25.4%, and 21.1% for American Indian, African American, White, and Asian, respectively. The amplification rates were 28.6%, 21.1%, 18.9%, and 12.5% for African American, Asian, White, and American Indian. Conclusions: There are many significantly mutated or amplified genes implicated in cervical cancer. Some of them are not grouped with the already known genes in relation to cervical cancer. For example, the KMT2C, SYNE1, KMT2D, EP300, RYR2, FLG, DMD, FBXW, MECOM, TRFC, RPL35A, LPP, TBL, FGF12, and SOX2 genes. They can be explored as therapeutic targets to improve cervical cancer treatment.
A path loss channel model for visible light communications in underground mines

Due to the ability to support communication and illumination simultaneously, visible light communication (VLC) system is considered as a potential access to realize effective communication in underground mines. In order to achieve this goal, it is necessary to understand the underlying physical propagation phenomenon in underground mines. Accurate and efficient channel models including large-scale fading characteristics are crucial for the design and performance evaluation of VLC systems. However, the characteristics of the underlying VLC channels have not been sufficiently investigated yet. In this paper, based on the recursive channel model, a path loss channel model is proposed precisely with the path loss exponent determined by three different trajectories in the mining roadway and working face environments. Taking different numbers of transmitters into account, both line-of-sight (LoS) and non-line-of-sight (NLoS) scenarios are considered. Our results demonstrate that the path loss exhibits a linear behavior in log-domain when curve fitting technique is applied. An expression for path loss as a function of distance is derived. Finally, root mean square (RMS) delay spread has been investigated and analyzed.
Statistical numeracy for health: a cross-cultural comparison with probabilistic national samples.

BACKGROUND Statistical numeracy is essential for understanding health-related risks and making informed medical decisions. However, this concept has not been investigated with probabilistic national samples or compared cross-culturally. We sought (1) to investigate differences in the level of statistical numeracy between 2 countries with different educational and medical systems-the United States and Germany; (2) to study the relationship between statistical numeracy and demographic characteristics such as age, sex, and education; and (3) to test whether a subjective measure of numeracy is a valid indicator of objective measures. METHODS In a survey of probabilistic, representative national samples in Germany and the United States, conducted in July and August 2008, we asked questions testing objective and subjective statistical numeracy. RESULTS German participants had higher numeracy skills than did US participants. On average, 68.5% (SE, 1.1%) and 64.5% (SE, 1.3%), respectively, of items testing objective numeracy were answered correctly. Subjective estimates of numeracy were a good indicator of the objective measures. There is a large gap in numeracy skills between persons with lower and higher educational levels, particularly in the United States. CONCLUSIONS Physicians should be aware that many patients may not understand all information relevant to making an informed decision. Fortunately, they can identify such patients and use nonnumerical presentation formats, such as graphical displays and analogies, to communicate important statistical information.
Nonlinear viscoelasticity and the Cox–Merz relations for polymeric fluids

This investigation concerns the important class of fluids whose rheological properties are described by a quasilinear viscoelastic constitutive equation of the Boltzmann superposition type. The first Cox–Merz relation is closely approximated by such a fluid if its nonlinearity in shear can be described by the strain measure , irrespective of the distribution of its relaxation times and, hence, its linear viscoelastic properties. Here γ equals the shear strain and J0 the zeroth-order Bessel function. The second Cox–Merz relation is met by materials with a different nonlinearity, namely S12(γ) = Si(γ), where Si is the sine integral. Experimental data on melts of a polystyrene and a low-density polyethylene sample were utilized to demonstrate that both Cox–Merz relations cannot hold simultaneously.
A Monte Carlo Study for Swamy ’ s Estimate of Random Coefficient Panel Data

particularly useful approach for analyzing pooled cross sectional and time series data is Swamy's random coefficient panel data (RCPD) model. This paper examines the performance of Swamy's estimators and tests associated with this model by using Monte Carlo simulation. The Monte Carlo study shed some light into how well the Swamy's estimate perform in small, medium, and large samples, in cases when the regression coefficients are fixed, random, and mixed. The Monte Carlo simulation results suggest that the Swamy's estimate perform well in small samples if the coefficients are random and but it does not when regression coefficients are fixed or mixed. But if the samples sizes are medium or large, the Swamy's estimate performs well when the regression coefficients are fixed, random, or mixed.
Microenvironment Responsive Modulations in the Fatty Acid Content, Cell Surface Hydrophobicity, and Adhesion of Candida albicans Cells

Considering the significance in survival and virulence, we have made an attempt to understand modulations in the membrane and cell wall properties of Candida albicans hyphae induced by temperature (37 °C) and neutral pH and yeast form cells grown under low hydrostatic pressure (LHP). Our results suggest that cell surface hydrophobicity (CSH) and adhesion are dynamic properties determined largely by the microenvironment rather than morphological forms, citing the significance of variation in niche specific virulence. GC-MS analysis showed that 49 and 41 fatty acids modulated under hyphal form induced by temperature alone (37 °C) and neutral pH, respectively while that of 58 under yeast form cells under low hydrostatic pressure (LHP) (1800 Pa). Fatty acid and ergosterol data indicates that fluidity increases with increase in temperature (37 °C) and neutral pH i.e., saturated fatty acids and ergosterol decreases. Similarly, CSH and adhesion decrease in response to temperature (37 °C), pH 7, and LHP compared to controls, irrespective of morphological forms. In general, membranes were more rigid, and cell walls were more hydrophobic and adhesive in yeast form compared to hyphal form cells, except in case of yeast form cells grown under LHP. Yeast form cells grown under LHP are less hydrophobic and adhesive.
Facilitating Postsecondary Transition and Promoting Academic Success Through Language/Literacy-Based Self-Determination Strategies.

Purpose As noted by Powell (2018), speech-language pathologists (SLPs) are an integral part of the overarching curriculum for all students in schools, and this holds true for adolescents who require transition planning. The purpose of this tutorial is to focus on transition planning for secondary school students with a language-based learning disability (LLD) and provide a case illustration for how SLPs may use self-determination strategies to facilitate postsecondary transition while promoting academic success. Method As students with LLD enter secondary school, they are expected to write and think at more complex levels than ever before to meet post-graduation workforce demands, yet the provision of needed language-literacy intervention services drastically declines. Teaching students with LLD self-determination skills, such as awareness of their own strengths and limitations, self-advocacy strategies, and self-regulation, is found to be related to positive post-school outcomes and can be readily integrated into transition planning by the SLP. Conclusion SLPs may ideally support secondary school student language-literacy needs in transition planning by using self-determination strategies to help access the curriculum and experience postsecondary success.
The validity and reliability of an iPhone app for measuring vertical jump performance

Abstract The purpose of this investigation was to analyse the concurrent validity and reliability of an iPhone app (called: My Jump) for measuring vertical jump performance. Twenty recreationally active healthy men (age: 22.1 ± 3.6 years) completed five maximal countermovement jumps, which were evaluated using a force platform (time in the air method) and a specially designed iPhone app. My jump was developed to calculate the jump height from flight time using the high-speed video recording facility on the iPhone 5 s. Jump heights of the 100 jumps measured, for both devices, were compared using the intraclass correlation coefficient, Pearson product moment correlation coefficient (r), Cronbach’s alpha (α), coefficient of variation and Bland–Altman plots. There was almost perfect agreement between the force platform and My Jump for the countermovement jump height (intraclass correlation coefficient = 0.997, P < 0.001; Bland–Altman bias = 1.1 ± 0.5 cm, P < 0.001). In comparison with the force platform, My Jump showed good validity for the CMJ height (r = 0.995, P < 0.001). The results of the present study showed that CMJ height can be easily, accurately and reliably evaluated using a specially developed iPhone 5 s app.
Feature Reinforcement Learning: Part I. Unstructured MDPs

Feature Reinforcement Learning: Part I. Unstructured MDPs General-purpose, intelligent, learning agents cycle through sequences of observations, actions, and rewards that are complex, uncertain, unknown, and non-Markovian. On the other hand, reinforcement learning is well-developed for small finite state Markov decision processes (MDPs). Up to now, extracting the right state representations out of bare observations, that is, reducing the general agent setup to the MDP framework, is an art that involves significant effort by designers. The primary goal of this work is to automate the reduction process and thereby significantly expand the scope of many existing reinforcement learning algorithms and the agents that employ them. Before we can think of mechanizing this search for suitable MDPs, we need a formal objective criterion. The main contribution of this article is to develop such a criterion. I also integrate the various parts into one learning algorithm. Extensions to more realistic dynamic Bayesian networks are developed in Part II (Hutter, 2009c). The role of POMDPs is also considered there.
Fragile X checklists: A meta‐analysis and development of a simplified universal clinical checklist

Clinical checklists available have been developed to assess the risk of a positive Fragile X syndrome but they include relatively small sample sizes. Therefore, we carried out a meta‐analysis that included statistical pooling of study results to obtain accurate figures on the prevalence of clinical predictors of Fragile X syndrome among patients with intellectual disability, thereby helping health professionals to improve their referrals for Fragile X testing.
Modulation of tryptophan environment in membrane-bound melittin by negatively charged phospholipids: implications in membrane organization and function.

Melittin is a cationic hemolytic peptide isolated from the European honey bee, Apis mellifera. Since the association of the peptide in the membrane is linked with its physiological effects, a detailed understanding of the interaction of melittin with membranes is crucial. We have investigated the interaction of melittin with membranes of varying surface charge in the context of recent studies which show that the presence of negatively charged lipids in the membrane inhibits membrane lysis by melittin. The sole tryptophan residue in melittin has previously been shown to be critical for its hemolytic activity. The organization and dynamics of the tryptophan residue thus become important to understand the peptide activity in membranes of different charge types. Wavelength-selective fluorescence was utilized to monitor the tryptophan environment of membrane-bound melittin. Melittin exhibits a red edge excitation shift (REES) of 5 nm when bound to zwitterionic membranes while in negatively charged membranes, the magnitude of REES is reduced to 2-3 nm. Further, wavelength dependence of fluorescence polarization and near-UV circular dichroism spectra reveal characteristic differences in the tryptophan environment for melittin bound to zwitterionic and anionic membranes. These studies are supported by time-resolved fluorescence measurements of membrane-bound melittin. Tryptophan penetration depths for melittin bound to zwitterionic and anionic membranes were analyzed by the parallax method [Chattopadhyay, A. , and London, E. (1987) Biochemistry 26, 39-45] utilizing differential fluorescence quenching obtained with phospholipids spin-labeled at two different depths. Our results provide further insight into molecular details of membrane lysis by melittin and the modulation of lytic activity by negatively charged lipids.
Development and In vivo Evaluation of Cefdinir Nanosus-pension for Improved Oral Bioavailability

Cefdinir belongs to III generation cephalosporins and is an oral extended spectrum antibiotic. It is a BCS class IV drug, with low solubility resulting in a low oral bioavailability of about 21% for capsules and 25% for suspension. The aim of this work was to develop cefdinir nanosuspension to improve the oral bioavailability. Nanosuspensions were prepared by using single stabilizer and combination of two stabilizers by employing high speed homogenization followed by sonication method and the prepared nanosuspensions were characterized. Initially, the drug excipient compatibility was checked by Differential Scanning Calorimeter (DSC). In trial experiments, tween80 concentration was varied from 0.25 to 0.75% and homogenization time was varied from 2.5 min to 10 min, and 0.5% surfactant concentration was found optimal. Further, trials were conducted with SLS and poloxamer 188 at the same concentration to know the role of stabilizers. Trials were also done by preparing cefdinir nanosuspensions with different techniques for comparative studies and their size and poly dispersity indices (PDI) were found. The mean size and zetapotential (ZP) of nanosuspensions, prepared by high speed homogenization followed by sonication varied from 541.7 to 947.2 and13.7mV to -22.4mV respectively. Results of saturation solubility and dissolution studies were used to optimize the nanosuspension. Optimized nanosuspension showed improved saturation solubility, dissolution rate and oral bioavailability by 1.752 fold when compared to marketed suspension and found to be stable at RT for 2 months.The bioavailability improvement was significant at a level of P value < 0.05 when student unpaired t-test was used. Hence, cefdinir nanosuspension formulation holds a great promise in improving dissolution rate and oral bioavailability.
U NIVERSALITY OF S TYLISTIC T RAITS IN T EXTS

The style of documents is an important property that can be used as discriminant factor in text mining applications. Among the great number of possible measures proposed to quantify writing style there are some features that can be characterized as universal, in the sense that they can be easily extracted from any kind of text in practically any natural language and provide accurate results when used in style-based text categorization tasks. In this paper we examine whether such universal stylometric features remain effective under difficult scenarios where the topic and/or genre of documents used in the training phase differ from that of the questioned documents. Based on a series of experiments in authorship attribution, we demonstrate that character n-gram features are reliable and effective given that the appropriate number of features is used. It is also shown that when the number of candidate authors increases, the representation dimensionality should also increase to improve classification results.
Parametrized measure models

This chapter represents the most important technical achievement of this book, a combination of functional analysis and geometry as the natural framework for families of probability measures on general sample spaces. In order to work on such a sample space, one needs a base or reference measure. Other measures, like those in a parametric family, are then described by densities w.r. t. this base measure. Such a base measure, however, is not canonical, and it can be changed by multiplication with an \(L^{1}\)-function. But then, also the description of a parametric family by densities changes. Keeping track of the resulting functorial behavior and pulling it back to the parameter spaces of a parametric family is the key that unlocks the natural functional analytical properties of parametric families. We develop the appropriate differentiability and integrability concepts. In particular, we shall need roots (half-densities) and other fractional powers of densities. For instance, when the sample space is a differentiable manifold, its diffeomorphism group operates isometrically on the space of half-densities with their \(L^{2}\)-product. The latter again yields the Fisher metric. At the end of this chapter, we compare our framework with that of Pistone–Sempi which depends on an analysis of integrability properties under exponentiation.
Estimation of Remaining Useful Life Based on Switching Kalman Filter Neural Network Ensemble

The proposed method is an extension of an existing Kalman Filter (KF) ensemble method. While the original method has shown great promise in the earlier PHM 2008 Data Challenge, the main limitation of the KF ensemble is that it is only applicable to linear models. In prognostics, degradation of mechanical systems is typically non-linear in nature, therefore limiting the applications of KF ensemble in this area. To circumvent this problem, this paper propose to approximate non-linear functions with piecewise linear functions. When estimating the RUL, the Switching Kalman Filter (SKF) is able to choose the most probable degradation mode and thus make better predictions. The implementation of the proposed SKF ensemble method is illustrated by implementing on NASA’s C-MAPSS Dataset as well as the PHM 2008 Data Challenge Dataset. The results show the effectiveness of the SKF in detecting the switching point between various degradation modes as well as the improved accuracy of the SKF ensemble method compared to other available methods in literature.
Neuroprotective Effect of Fucoidan against N-methyl-D-aspartate-Induced Excitotoxicity in Rat Hippocampus

Fucoidan, a sulfated polyanionic polymer of L-fucose, is obtained from brown marine macroalgae. In the present study, neuroprotective effect of fucoidan against N-methylD-aspartate (NMDA)-induced excitotoxicity in the hippocampus was investigated. The patch clamp study revealed that fucoidan significantly inhibited NMDA receptor-activated ion current in the acutely dissociated hippocampal CA1 neurons. In an organotypic hippocampal slice culture, fucoidan inhibited NMDA-induced neuronal cell death in a dose-dependent manner. The present study showed that fucoidan possesses a neuroprotective effect against NMDA-induced excitotoxicity, and that the suppressive effect of fucoidan on the NMDA-induced ion current can be suggested as being the underlying neuroprotective mechanism of fucoidan.