Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFECT OF ZIZIPHUS SPINA CHRISTY ON BIOFILM FORMATION OF METHICILLIN RESISTANCE STAPHYLOCOCCUS AUREUS AND STAPHYLOCOCCUS HAEMOLYTICUS

This research aimed to investigate the antibacterial activity of hot an aqueous extract of leaves Ziziphus spina Christy (Sidr), against biofilm formation of clinical isolates Staphylococcus aureus and Staphylococcus haemolyticus. Ten isolates were obtained from the laboratory of microbiology in the Department of Biology, Faculty of Education for Women, the isolates were diagnosed initially as Staphylococci and then selected four isolates depending on virulence and resistance to different types of antibiotics. After that VITEK-2 compact system (ID and AST) was used to confirm the species of Staphylococci. The results showed that three isolates reverting to Staphylococcus aureus and one to Staphylococcus haemolyticus. Investigation of S. aureus and S. haemolyticus isolates ability to forming biofilm by using of Microtiter plate (96 well) methods. The results indicated that all of the isolates were able to produce the biofilm. The effect of Moxifloxacin and Penicillin G with (MIC), (Sub-MIC) and (Sub-Sub-MIC) were detected for preventing of S.aureus and S.haemolyticus biofilm production, as well as hot an aqueous extract of leaves Ziziphus spina Christy (Sidr) with 50 mg/ml tested against the biofilm formation, the results showed ability of tow antibiotics and plant extract to prevent biofilm formation. The synergism effect of penicillin G, Moxifloxacin with (MIC), (Sub-MIC) and (Sub-Sub-MIC) and hot an aqueous extract of leaves Ziziphus spina christi (Sidr) with 50 mg/ml investigated, the results revealed that high synergism effect between two antibiotics and plant extract.
Contrastive Attribution with Feature Visualization

Towards the goal of presenting contrastive explanations for the output of a classiﬁer, we present a method for ﬁnding contrastive foils in feature space and then visualizing in data space for easy interpretation. To produce a simple classiﬁer for this method, we present a model that combines decision trees with supervised variational autoen-coders using our new differentiable decision tree . This allows for end-to-end optimization of a deep network to perform feature extraction from structured, high-dimensional data for classiﬁcation by a single decision tree. Our experiments demonstrate that the resulting model is satisfactory in both classiﬁcation and image generation and can explain a model’s reasoning in answering a number of questions on classiﬁcation and instance generation. Further experiments demonstrate that the model produces explanations using features that align with human-produced labels without any prior access to those labels.
An approachable analytical study on Educational Data Mining

- Data mining is the process of extracting evocative information and to develop significant association amid variables accumulated in data warehouse. It is a computational process of discovering patterns from huge databases and focuses on mining knowledge from the available data. Mining in educational environment is called educational data mining that is concerned with developing novel methods to discover knowledge from educational database. Educational data mining is an emerging research area that applies assorted tools and techniques of data mining to discover data in the field of education. It focuses on discover new patterns in captured data, developing novel algorithms or models for the escalation of education environment. This paper has fourfold objective. Firstly, it focuses on educational data mining as an emerging area with the combination of data mining and educational data. Secondly, it throws light on EDM process that applies data mining techniques to design educational systems. Thirdly, it considers all the EDM components to attain the educational objectives. Lastly, it concentrates on future research of EDM field viz. developing user-friendly mining tools, developing decision supports and recommendation engines and standardization of methods and data.
Degradation of Plant Lignin by Pseudomonas sp. Strain YS-1p And Phanerochaete chrysosposium RP-78 Co-Cultures

Delignification is a critical step in the bioconversion of lignocellulosic biomass into useful monomers. Fungi and bacteria both have evolved pathways to degrade lignin and are known to play active roles in decomposition of plant biomass. However, little efforts have been made to study them together as an integrated microbial system. There is limited knowledge about what specific roles they play and what kind of interactions they have during the decomposition process. The major focus of this research is to study lignin degradation using Pseudomonas sp. strain YS1p (bacteria) and Phanerochaete chrysosporium RP-78 (fungi) when inoculated as individual cultures as well as in co-cultures in mineral salts medium supplemented with plant biomass: sugarcane bagasse and sorghum bagasse. Flasks were inoculated with strain RP-78 (F) and strain YS-1p (B) at various fungal-to-bacterial ratios including 0:1, 1:0, 1:1, 1:10 and 1:50, respectively. Flasks were sacrificed periodically and monitored for population dynamics. Culture supernatant was assayed for major lignin degrading enzymes including lignin peroxidase, dyp peroxidase and laccase. Additionally, extracellular enzymes were concentrated and subjected to 1-D PAGE-LCMS/MS for proteome analysis, while recovered plant biomass was used for Py-GC/MS analysis. Our results show that Pseudomonas grew best in co-cultures with P. chrysosporium whereas the growth of latter was suppressed in the presence of bacteria. This also affected their abilities to produce extracellular enzymes involved in lignocellulose degradation as shown by our results of proteome analysis. Most of the enzymes involved in degradation of lignin, cellulose and hemicellulose were produced by the fungi, while the bacteria produced few enzymes at low levels. This suggests that bacteria were able to derive benefit from fungal enzymes for accessing degradation products and promoting their growth without contributing as much to the degradation process. Enzyme activities of lignin degrading enzymes showed that the two peroxidases: Lip and Dyp were expressed maximum in co-cultures while laccase was expressed in highest amounts in bacterial monocultures. Furthermore, analysis of plant biomass by Py-GC/MS revealed that microbial pretreatment altered the composition of lignocellulose in plant biomass with plant biomass showing significant decrease in lignin derivatives than in untreated controls.
Cramér-Rao lower bound and maximum-likelihood estimation in ptychography with Poisson noise

We investigate the performance of ptychography with noisy data by analyzing the Cramer Rao Lower Bound. The lower bound of ptychography is derived and numerically computed for both plane wave and structured illumination. The influence of Poisson noise on the ptychography reconstruction is discussed. The computation result shows that, if the estimator is unbiased, the minimum variance for Poisson noise is mostly determined by the illumination power and the transmission function of the object. Monte Carlo analysis is conducted to validate our calculation results for different photon numbers. The performance of the maximum likelihood method and the approach of amplitude-based cost function minimization is studied in the Monte Carlo analysis also.
Automatic Publication of Open Data from OGC Services: the Use Case of TRAFAIR Project

This work proposes a workflow for the publication of Open Spatial Data. The main contribution of this work is the automatic generation of metadata extracted from Open Geospatial Consortium (OGC) spatial services providing access to feature types and coverages. Besides, this work adopts a geospatial extension of the Data Catalog Vocabulary metadata application profile for data portals in Europe for the description of datasets. This extension, called GeoDCAT-AP, has been adopted because it allows for an appropriate crosswalk between the annotation requirements in the spatial domain and the metadata models accepted in general Open Data portals. The feasibility of the proposed workflow has been tested within the framework of the TRAFAIR project to publish monitoring and forecasting air quality data. Keywords–Environmental data; Open Data; GeoDCAT-AP; metadata; geospatial services; OGC.
Phosphorus Determination after Mehlich 3 Extraction and Anion Exchange Resin in an Agricultural Soil of Northwestern Spain

Differences in soil phosphorus (P) contents measured by various techniques may have implications for agronomic and environmental testing. Reduced-tillage systems combined with surface manure application increase the potential risk of nutrient losses by surface runoff. A field trial was conducted to evaluate the effect of livestock slurry on nutrient accumulation at the surface layer of an acidic soil rich in organic matter with excess P levels and loamy texture. Two reduced-tillage systems, no tillage (NT) and minimum tillage (MT), and four different fertilizer treatments were assessed. The amounts of P extracted by anion-exchange resin (AER) and by Mehlich 3 (M3) were compared; in addition, differences between two determination methods of P contents extracted by Mehlich 3, namely molybdic acid colorimetric standard procedure (M3-COL) and inductively coupled plasma–mass spectroscopy (M3-ICP), were evaluated. Ninety-six soil samples were taken from the 0- to 5-cm surface layer in three successive dates after increasing manure addition. Colorimetric Mehlich 3 P ranged from 49 to 431 mg dm–3. The ranks of mean extractable soil P concentrations were AER < M3-COL < M3-ICP. The linear correlation coefficient between M3-COL and M3-ICP was highly significant (R2 = 0.89; P < 0.01), but a two-straight-lines model or a quadratic relationship were more adequate for describing the dependence between the two determination procedures after M3 extraction. Relative and absolute differences between M3-COL and M3-ICP showed a tendency to increase as organic carbon content increased. Phosphorus content extracted by AER and M3-COL or M3-ICP reported a significant but much less predictable relationship with R2 values of 0.27 and 0.21 (n = 96), respectively. The P in the surface layer accumulated more under NT than under MT.
Development of enrofloxacin ELISA using a monoclonal antibody tolerating an organic solvent with broad cross-reactivity to other newquinolones

Abstract Antibacterial reagents, especially quinolones, are widely used in animals and humans, and have caused serious problems to human health because of their residual contaminants in food. In order to screen for different kinds of newquinolones at the same time, a sensitive and specific enzyme-linked immunoassay (ELISA) has been developed. The anti-enrofloxacin monoclonal antibody was selected because of its ability to react with structurally related newquinolones in organic solvent. The antibody has 100% cross-reactivity with norfloxacin, ciprofloxacin and other newquinolones at 50% inhibition of control values IC50, but not with nitroflazone, sulphadimethoxine. The lowest detection limit of this ELISA was 0.7 ng/ml (ppb) when enrofloxacin was used as the calibrator. Eel extracts were spiked with enrofloxacin and the average recoveries at 10, 50, 100 ng/ml were 98, 102 and 91%, respectively. The proposed ELISA is a useful method for the practical microquantitation of various newquinolones in biological and environmental specimens.
Screening for Depressive Symptoms amongst Patients with Diabetic Peripheral Neuropathy

AIM: The study aimed to determine if there is a relationship between having diabetic peripheral neuropathy and the development of depressive symptoms in patient with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHOD: A comparative non-experimental study was conducted. Ninety-five T2DM individuals aged 65 years and more were recruited. The sample was divided into two groups: 50 participants with T2DM only and 45 participants with DPN. The Patient Health Questionnaire-9 (PHQ-9) was used to collect information about low mood/ depression symptoms in the recruited subjects. RESULTS: Participants with DPN recorded higher scores of PHQ-9 than those with T2DM only. The mean PHQ 9 score for the Diabetic Peripheral Neuropathy group (6.09) was significantly higher than the mean PHQ 9 score for the T2DM group (2.24) (p<0.001). Participants with DPN were more likely to have a mild/moderate or moderately severe low mood/ depression symptoms, when compared to Type 2 DM participants who exhibited minimal to no low mood/depressive symptoms. CONCLUSION: The association between diabetic neuropathy and depression is confirmed, with significant depressive symptoms found in patients with neuropathy when compared to patients with diabetes with no complications. Therefore, complaints caused by DPN and emotional problems associated with DPN should be addressed in the management of DPN in order to prevent depressive symptoms. A call for change in screening practices to help identify patients with DM and depressive symptoms is warranted.
Teaching Lexicography as a University Course: Theoretical, Practical and Critical Considerations

This paper offers an account of a university course in Lexicography, designed particularly for advanced EFL students. The discussion and accompanying material derive from around fifteen years of the author's experience in developing and teaching this course. The aims of the paper are twofold: firstly, to draw attention to the fact that lexicography today is no longer just 'the art and craft of' dictionary making of yesteryear but a fully-fledged applied linguistic discipline, with its own theory, methodology and practice, some of which is teachable as a dedicated academic subject; and secondly, to encourage the teaching of practical and theoretical lexicography to university students by putting forward concrete proposals. The exposition is divided into five parts, as follows: Section 1 brings some opening remarks, including that on the scientific status of lexicography; Section 2 reviews theoretical aspects regarding the design of this course; Section 3 describes practical aspects regarding the implementation of the course; Section 4 examines critical aspects regarding the evaluation of the course; and Section 5 recapitulates the main points of the paper and projects the modifications to the course in the future.
Optical response of Ag‐induced reconstructions on vicinal Si(111)

The optical response of the Si(111)‐(3 × 1)–Ag surface has been studied for the first time with reflectance anisotropy spectroscopy (RAS). A single domain surface was obtained by depositing <1 ML of Ag onto a vicinal Si(111) substrate at 870 K. A significant optical anisotropy develops around 2.2 eV which is related to the formation of the 3 × 1 structure. This surface was then used as a template to grow one‐dimensional (1D) arrays of Ag nanodots, and also 3D Ag islands, by depositing 0.5 ML, and higher, coverages of Ag at room temperature. RAS of these structures showed a different response in the 2.2 eV region, with a broadened and reduced anisotropy. By extending the RA spectra into the infra‐red region (0.5–1.5 eV), substantial differences between the structures were observed below 1 eV, which may be linked to a difference in the metallic character of the nanodots and islands. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Remineralizing Efficacy of Biomimetic Self-Assembling Peptide on Artificially Induced Enamel Lesions (In vitro Study)

Background: The technology of self-assembling peptides have been progressed as an alternative remineralizing agent to fluoride, that assemble into a fibrillar three-dimensional scaffold. Aim: To investigate the effectiveness of self-assembling peptide (P11-4) on enamel remineralization both alone and in combination with flouride compared to fluoride-based delivery systems and casein phosphopeptide-amorphous calcium phosphate fluoride (CPP-ACPF). Materials and Methods: Enamel caries-like lesions were created artificially on the buccal surfaces of 25 extracted human maxillary first premolars of permanent teeth. Specimens were randomly arranged into five groups (n = 5) based on the remineralizing agent used: Group 1–control: Artificial saliva, Group 2 – fluoride varnish, Group 3 – CPP-ACPF varnish, Group 4–self-assembling peptide agent, Group 5 - double application group (self-assembling peptide and fluoride). The application of all the materials was according to their producer's instructions and the storage of the specimens were in artificial saliva that renewed daily. Assessment of surface microhardness (SMH) was done at baseline, after demineralization and after 2weeks of remineralizing agents’ application, then the data were analyzed using ANOVA and paired t-test. Results: Although, no significant difference in decrement in enamel microhardness between flouride, self-assemblig peptide and the double application group, while it was significantly higher in these groups when compared to CPP-ACPF. In addition, the control group revealed, no statistically significant difference in mean of enamel microhardness after remineralization compared to that after demineralization. Conclusions: Self-assembling peptide alone and its combination with fluoride varnish, both have the same remineralizing efficacy, showing an encouraging, noninvasive regeneration potential as an alternative remineralizing agent to fluoride.
Cavitation Erosion of HVOF Metal-ceramic Composite Coatings Deposited onto Duplex Stainless Steel Substrate

ILARE BORDEASU1*, LAVINIA MADALINA MICU2*, ION MITELEA1, ION DRAGOS UTU1, LIVIU DANIEL PIRVULESCU1, NICUSOR ALIN SIRBU3, 1University Politehnica Timisoara, 2 Victoriei Sq. , 300006, Timisoara, Romania 2Banat University of Agricultural Sciences and Veterinary Medicine, 119 Calea Aradului, 300645 Timisoara, Romania 3National R & D Institute for Welding and Material Testing ISIM Timisoara, 30 Mihai Viteazul Blv, 300222, Timisoara, Romania
Predicting Customer Behavior With Activation Loyalty per Period. From RFM to RFMAP

Objective: Identify a new model of predicting customer behavior based on new variables that can be used by marketing management and adapted to their business planning. Methodology: New model has been used, with the definition of new calculation systems of the traditional variables R, Recency, F, Frequency, and M, monetary value, (RFM), related to the business periods. Besides, activation in each period P becomes a key variable for constructing the purchase cohorts of customers and identifying their potential. A new variable, Activation Loyalty, is recognized as a good proxy of the likelihood of future customer purchases. The model builds a weighting through a multiple regression analysis obtaining β for each variable, including the periods of activation, presenting the relative effect of the variables, and the best global explanation of the model. Results: This new model, RFMAP, which includes Activation Periods and Activation Loyalty, presents a higher prediction accuracy and improvements over traditional models with a clear impact, useful and manageable lines of segmentation, and prioritization for marketing management in CRM systems. Limitations: The main limitation of this model consists that it is based on data of only one company, and it should show the value in other sectors and give a full insight through its transversal application. Practical implications: The involved advantages demonstrated better predictability and usefulness to decision-makers, not only to determine the best customers but also with lapsed ones. It gives a meaningful explanation of differences in customer behavior, which are present in the data and are being reflected in the model. Also, it provides a prescriptive prioritization of variables to be managed in the marketing plan and how to be implemented.
A Fixed-Time Convergent Distributed Algorithm for Strongly Convex Functions in a Time-Varying Network

This paper presents a novel distributed nonlinear protocol for minimizing the sum of convex objective functions in a fixed time under time-varying communication topology. In a distributed setting, each node in the network has access only to its private objective function, while exchange of local information, such as, state and gradient values, is permitted between the immediate neighbors. Earlier work in literature considers distributed optimization protocols that achieve convergence of the estimation error in a finite time for static communication topology, or under specific set of initial conditions. This study investigates first such protocol for achieving distributed optimization in a fixed time that is independent of the initial conditions, for time-varying communication topology. Numerical examples corroborate our theoretical analysis.
Exact results for the optical absorption of strongly correlated electrons in a half-filled Peierls-distorted chain

Abstract In this, the second of three articles on the optical absorption of electrons in a half-filled Peierls-distorted chain, we present exact results for strongly correlated tight-binding electrons. In the limit of a strong on-site interaction U, we map the Hubbard model onto the Harris-Lange model which can be solved exactly in one dimension in terms of spinless fermions for the charge excitations. The exact solution allows for an interpretation of the charge dynamics in terms of parallel Hubbard bands with a free-electron dispersion of bandwidth W, separated by the Hubbard interaction U. The spin degrees of freedom enter the expressions for the optical absorption only via a momentum-dependent but static ground-state expectation value. The remaining spin problem can be traced out exactly since the eigenstates of the Harris-Lange model are spin degenerate. This corresponds to the Hubbard model at temperatures large compared with the spin exchange energy. Explicit results are given for the optical absor.
The effect of tax revenues on GDP growth in Jordan

Article history: Received: October 29, 2020 Received in revised format: November 27 2020 Accepted: December 15, 2020 Available online: December 15, 2020 The research aims to identify the impact of tax revenues on the growth of the gross domestic product (GDP) in Jordan during the period 2000-2018. The research reaches a set of results, which is that the greater the value of tax revenues by one unit, the greater the value of the GDP in Jordan by 7.257 units during the same period. There is also a positive effect of tax revenues on the growth and increase of the GDP in Jordan, however, there is no common integration between tax revenues and the GDP in Jordan. Moreover, there is a correction from the short term to the long term and there is an effect of the long-term correction of the relationship between tax revenues and the GDP during the study period. The study recommends the need to work to facilitate the procedures for individuals to pay taxes through modern technological means, work to develop and simplify tax services and raise the level of transparency in tax dealings with all individuals, the need to make amendments to the tax law in order to match the living conditions of individuals and achieve the highest efficiency in collecting due taxes, increasing tax exemptions that are offered to foreign investment to encourage them for investments in all economic, commercial, service and industrial fields in Jordan, working to diversify sources of income for the Jordanian economy and not to rely entirely on tax revenues as a primary source of income. © 2021 by the authors; licensee Growing Science, Canada