Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibiogram Analysis and Characterization of Bacterial Pathogens from Leucorrhea Patients

In recent research work bacteria were isolated from samples of leucorrhea patients admitted in Lady Wellington hospital Lahore (gynae ward) and Basheer welfare hospital Shahdara Lahore. The sampling was done from pregnant and non-pregnant leucorrhea patients aged 18 to 30 years by using sterile culture sticks from vagina. The samples were spread on agar plates and incubated for overnight, bacterial strains were isolated by streak plate method. The strains were named L1, L2, L3 and L4. Identification was carried out by various morphological and biochemical tests. Molecular characterization was also done to characterize bacteria up to species level. L1 strain was identified as Streptococcus pyogens, L2 as Staphylococcus aureus, L3 as Neisseria gonorrheae and L4 as Escherchia coli. Antibiotic resistance was analyzed by disc plate method. L1, L2 and L3 strains showed maximum sensitivity with Cefepime antibiotics having values 17.74 µg/ml, 13.63 µg/ml and 12 µg/ml respectively. L4 showed max sensitivity with Azithromycin and Cloxacillin antibiotics i.e., 6.25 µg/ml and 6.4 µg/ml respectively. Optimum pH was 6.5 for L1 and L2, while 7 for L3 and L4. Optimum temperature was 37 for all strains.
A fuzzy decision support for the selection of information system outsourcing company

The outsourcing of information systems can not only reduce installation cost, but also allow a company to focus more on its core competence. Being sure of selecting the best contractor can increase the likelihood that information system outsourcing will be a success. This study uses the fuzzy concept to develop a decision support system which can help decision-maker to get a better judgement and with the explanations for the result. Via implementing this system, we not only can select the best one contractor among the outsourcing information service companies, but also the information service companies can assess themselves to adjust or improve the caused factors if the aggregative capability does not meet the needs.
DOUBLE CLUSTERING METHOD IN HIDING ASSOCIATION RULES

Association rules are among important techniques in data mining which are used for extracting hidden patterns and knowledge in large volumes of data. Association rules help individuals and organizations take strategic decisions and improve their business processes. Extracted association rules from a database contain important and confide individuals may be threatened. Therefore, the process of hiding sensitive association rules should be performed prior to sharing the database. This is done through changing the database transactions. Thes all sensitive association rules are hidden and a maximum number of non association rules are extractable from the sanitized database. In fact, a balance is to be established between hiding the sensitive r rules. A new algorithm is presented in this paper to create a balance between preserving privacy and extracting knowledge. The items of sensitive rules are clustered in the proposed algorithm, in order to reduce change of changes and clustering of rules are applied in order to reduce the side effects of the hiding process on non
Blocking probability of three-stage multicast switches

In this paper, an analytical model for the evaluation of the blocking probability of a three stage STM switch in presence of multicast is presented. The basic characteristics of this model are: (i) the elementary switches can assume any size; (ii) multicast connections can be characterised by any fan-out distribution; (iii) both single request and additive request scenarios are analysed. Moreover, three network operation alternatives are analysed, i.e. multicasting is carried-out in: (a) the first and the third stages; (b) the second and the third stages; (c) all the three stages. The model uses a mixed approach derived from approaches proposed by Lee (1955)and Jacobeus (1950). The analytical results are compared with those arising from simulation. The good accordance of the two series of results demonstrates the soundness of the model assumptions.
OPEN DOMAIN QUESTION ANSWERING SYSTEM USING SEMANTIC ROLE LABELING

The World Wide Web is an attractive source of information retrieval and can be used for seeking simple factual answers for user questions. Although usual information retrieval systems like search engines helps in finding the relevant documents for a set of keywords, there are situations where we have more specific information need. Search engines only provide the actual facts as a ranked list of documents and links that contain the keywords. However, what a user really wants is often a precise answer to a question. A Question Answering system gives us a precise solution to this scenario. A Question Answering system retrieves a precise answer to any natural language question posed by the user. A typical QA system uses several language processing techniques. In this paper, an Open Domain Question Answering that answers simple Wh-questions using online search has been proposed.
Early Transplantation of Human Umbalical Cord Blood Stem Cell Can Improve Engrafment and Liver Response to Carbon Tetra Chloride induced Cirrhosis in Mice

Background: The potential use of UCB in the treatment of hepatic failure (a major problem worldwide) has been a research focus for several years now. Recent studies have identified UCB as a possible source of hepatic progenitor cells that can be differentiated into hepatocyte in vitro and in vivo and can ameliorate fibrosis. Objectives: the aim of this study was to investigate the hepatic response to transplantation of HUCB stem cells in CCl4 injured liver in mice, as regard liver function, histopathology and immunohistochemistry. Design: Experimental study. Setting: The stem cell unit in the Physiology Department and the animal house after cord blood collection in the Gynecology and Obstetric department, Faculty of Medicine, Suez Canal University. Materials and Methods: Hepatic fibrosis was induced by CCl4. HUCB stem cells were infused systemically through the tail vein immediately (group 1), and after one week of receiving CCl4 (group 2), Group 3 received only CCl4 (as a control group). Administration of CCl4 was continued for 10 weeks in G1, G2 and G3, while group 4 (as another control group) received only the solvent of CCl4 for 10 weeks. After that, blood from all groups was collected for assessment of liver function, then all mice were sacrified under general anesthesia and the liver was fixed and prepared for histopathological and immumohistochemical examination. Results: It was found that the level of alanine aminotransferase (ALT) in mice treated with stem cells after CCl4 administration was significantly lower while serum albumin was significantly higher compared to group 3 animals who received CCl4 without stem cells treatment (P= 0.001). Whereas serum total and direct bilirubin levels were similar among all groups. histopathological examination revealed that hepatic damage was less in the stem cells treated mice (G1 and G2) than in non treated group (as regards liver cell changes, portal tract inflammation, piecemeal necrosis, portal tract fibrosis and bridging fibrosis). However, liver inflammation and fibrosis were more in mice treated after one week than in immediately treated mice. Immumohistochemical examination, more importantly, IHC staining with monoclonal mouse anti-human hepatocyte revealed presence of human hepatocytes in injured mice liver which proved that the transplanted stem cells were transdifferentiated into hepatocyte. Conclusion: HUCB stem cells were transdifferentiated into hepatocyte when infused in mice injured liver and cause improvement in liver function test and liver histology.
VARIABLE IMPEDANCE CONTROL OF A PARALLEL ROBOT FOR ANKLE REHABILITATION

This paper proposes a novel variable impedance controller for a redundantly actuated parallel robot to allow execution of passive ankle rehabilitation exercises while taking into consideration of human biomechanics online. By using a biomechanical model of the human ankle which describes the kinematics and dynamics of the ankle foot structure, the kinematic parameters of the ankle can be estimated online to allow identification of the constrained direction of motion. Impedance adjustment heuristics were also formed by investigating the ankle stiffness over a range of joint displacements through the use of the ankle model developed. The variable impedance controller can prevent application of excessive actuator forces which could threaten the safety of the patient.
Novel preoperative nutritional assessment tool and prognostic model for ESCC patients

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive tumor types worldwide, and malnutrition prevails in these patients. However, there is no preoperative nutritional assessment tool specifically designed for patients with ESCC. Methods: Patients who received esophagectomy from 2004 to 2016 were consecutively included. The preoperative nutritional risk factors for ESCC were screened by univariate and multivariate Cox regression analysis to construct a new nutritional scoring tool. A prognostic model of ESCC based on the new scoring tool was further proposed. Results: A total of 510 ESCC patients were enrolled. A novel BLUT (BMI-lymphocyte-uric acid-triglyceride) scoring tool based on BMI, lymphocyte count, uric acid level, and triglyceride level was proposed, which could effectively predict the prognosis of ESCC patients (log rank P<0.001), and it was better than the traditional nutritional assessment tools. The C-index and 95% confidence interval (CI) of the nomogram based on the BLUT scoring tool was 0.735(0.698-0.772). It had good prognostic efficacy and was significantly better than the model based on T stage and N stage (P=0.038). The calibration curve of internal and external validation suggested a good fitting effect with the real situation in judging the 1-year, 3-year, and 5-year survival status. Conclusions: The BULT scoring tool could distinguish the heterogeneity of preoperative nutritional status and the BLUT-based nomogram had good prognostic performance for ESCC patients.
Neurovascular reactivity in patients with focal epilepsy

Background: Complex neurovascular activation by transcranial Doppler (TCD) has not been presented at the moment in drug-responsive patients with focal epilepsy. The objective of this study is to assess the neurovascular activation to complex visual stimulation of drugresponsive patients with focal epilepsy during interictal period. Methods: Twenty-five patients with focal epilepsy and 25 healthy subjects were screened for this study in our Neurosonology Laboratory. We performed transtemporal TCD recordings from the P2-segments of both posterior cerebral arteries (PCA) simultaneously during complex visual stimulation, at least, ten days after last epileptic attack. The individual reactivity was defined as a relative increase of the blood flow velocities as a percentage change of the baseline values. Results: Most of the patients have an epileptic focus in the temporal lobe documented by the EEG. The Doppler data of the epileptic sides and non-epileptic sides were analysed separately. The complex visual reactivity was significantly higher at the epileptic side in the patients (52.5%) from those of the controls (36.8%) (p=0.002). Discussion: In contrast to the earlier reports of the studies that were found diminished neurovascular reactivity to simple or complex visual stimulation using TCD, our study showed the temporal and occipital region of the patients with focal epilepsy have hyperactive neurovascular units at the epileptic side during the interictal period when comparing with the healthy subjects. However, to emphasise the importance of investigating neurovascular coupling in further studies are needed.
EFFECT OF DIALYSATE TEMPERATURE ON HEMODYNAMIC STABILITY AMONG HEMODIALYSIS PATIENTS

Background Hypotension is one of the complications of hemodialysis treatment. It increases morbidity and mortality and can compromise the dialysis efficacy. Cooling the dialysate below 36.5°C is an important factor that contributes to hemodynamic stability in patients during hemodialysis. Objective To assess the effect of dialysate temperature on hemodynamic stability during hemodialysis sessions, post dialysis fatigue and the adequacy of dialysis. Methods A total of 40 patients were assessed during six dialysis sessions; in three sessions, the dialysate temperature was (37 °C) and in three other sessions, the dialysate temperature was (35 °C). Specific scale questionnaires were used in each dialysis session, to evaluate the symptoms during the dialysis procedure as well as post-dialysis fatigue, and respective scores were noted. Blood pressure, heart rate, temperature were recorded. Also dialysis efficacy using Kt/v, urea reduction ratio were measured. Results The results showed that usage of low dialysate temperature was associated with the following : higher post dialysis systolic blood pressure (P < 0.05) and lower post dialysis heart rate (P < 0.05), better intradialysis symptoms score and post-dialysis fatigue scores (P < 0.05 and P < 0.05, respectively), shorter post-dialysis fatigue period (P < 0.05) as well as Similar urea removal and Kt/V . Conclusion Cool dialysis is an important factor in hemodynamic stability during hemodialysis. Also it improves symptoms during and after hemodialysis. Cool dialysis has no effect on adequacy of dialysis.
CONTRAST IMPROVEMENT OF SATELLITE IMAGES USING DWT AND SHARPNESS PRESERVING ALGORITHMS

This paper present contrast enhancement technique for satellite images using dwt and sharpness preserving algorithms. The images taken from satellites are used for a variety of applications but the images taken are not very enhanced and may contain blurry or less contrast. Despite the growing demand for better remote sensing images different methodology was proposed but they are not able to preserve edge details and saturation of the images having low and high intensity areas. Histogram equalization (HE) has been the most popular approach to enhancing the contrast in various applications. But cannot maintain edge detail and cannot preserve the average brightness of the image, which can be under-or over-saturation in the processed image. The proposed algorithm overcomes this problem using the efficient technique used for enhanced the contrast of satellite images using decomposition of dominant brightness level, adaptive intensity transfer function, boundary smoothing and canny edge detection techniques. Experimental results shows, that the proposed algorithm improves the contrast and the perspective of the local details is better than existing techniques and preserves the edge detail in the image. The proposed method can effectively enhance any low-contrast images and maintain the edge contingent acquired by a satellite camera and is also suitable for other various imaging devices such as consumer digital cameras, photorealistic 3-D reconstruction systems, and computational cameras.
An application of spectral analysis to weld penetration detection

High quality welded seams require the material to be joined to be fully molten from the front surface to the back. Most quality control systems require access to the back surface of the join. In many situations, for example pipe joining, only the front surface is accessible. This paper describes a front surface penetration detection technique without the introduction of transducers into the harsh environment of the arc. The arc itself is used to both excite oscillations of the penetrated pool and to monitor the surface displacement. A least squares Prony model is developed for this surface oscillation in which the existence of decaying sinusoids within the motion signify a fully penetrated pool. Arc noise contributions are separated from signal components by Singular Value Decomposition (SVD) and use of both forward and backward prediction in the modelling. Performance of the technique is assessed by application to real arc-pool data.
The effect of Scratch environment on student's achievement in teaching algorithm

800x600 In this study, the effect of Scratch environment in teaching algorithm in elementary school 6th grade Information and Communication Technologies course was examined. The research method was experimental method. Control group, pretest-posttest design of experimental research method and a convenience sample consisting of 60 6th grade students were used. The research instrument was achievement test to determine the effect of Scratch on learning algorithm. During the implementation process experiment group studied using Scratch and control group studied with traditional methods. The data was analyzed using independent-samples t-test, paired-samples t-test and ANCOVA statistics. According to findings there is no statically significant difference between posttest achievement scores of experiment and control groups. Similarly, In terms of gender there isn’t a statically significant difference between posttest scores of experiment and control groups. Keywords: distributed learning environments, programming and programming languages, elementary education Normal 0 21 false false false TR X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";}
Rigidity analysis for modeling protein motion

Rigidity Analysis for Modeling Protein Motion. (May 2010) Shawna Lynn Thomas, B.S., Texas A&M University Chair of Advisory Committee: Dr. Nancy M. Amato Protein structure and motion plays an essential role in nearly all forms of life. Understanding both protein folding and protein conformational change can bring deeper insight to many biochemical processes and even into some devastating diseases thought to be the result of protein misfolding. Experimental methods are currently unable to capture detailed, large-scale motions. Traditional computational approaches (e.g., molecular dynamics and Monte Carlo simulations) are too expensive to simulate time periods long enough for anything but small peptide fragments. This research aims to model such molecular movement using a motion framework originally developed for robotic applications called the Probabilistic Roadmap Method. The Probabilistic Roadmap Method builds a graph, or roadmap, to model the connectivity of the movable object’s valid motion space. We previously applied this methodology to study protein folding and obtained promising results for several small proteins. Here, we extend our existing protein folding framework to handle larger proteins and to study a broader range of motion problems. We present a methodology for incrementally constructing roadmaps until they satisfy a set of evaluation criteria. We show the generality of this scheme by providing evaluation criteria for two types of motion problems: protein folding and protein transitions. Incremental Map Generation eliminates the burden of selecting a sampling density which in practice is highly sensitive to the protein under study and difficult to select. We also generalize the
A fitted B-spline method to derive a representative 3D axis from a set of multiple road traces

Abstract Collecting data to make an accurate representation for roads is an expensive process. Nevertheless, there is a collaborative alternative for this endeavour. Many drivers, bicyclists and even pedestrians have consumer-grade GPS (low precision) on their smartphones or electronic devices. Those users could transfer their road or track itineraries to a large database in order to compute the accurate geometry of any route. For each road or track, the large database would have many traces from which to infer an accurate representative 3D axis. Several inference methods have been proposed but most of them to fit the 2D trace data set. We propose to create a set of ordered points from the 3D trace data set and then using the least-squares method, to fit a B-spline curve to those points. The resulting parameterized curve will be a good representative 3D axis of the traces. Our method considers the nodes to be evenly separated and allows the system to recommend the number limit of nodes necessary to reach the convergence.
Adverse Childhood Experiences Indirectly Affect Child Telomere Length Through Self-Regulation

ADVERSE CHILDHOOD EXPERIENCES INDIRECTLY AFFECT CHILD TELOMERE LENGTH THROUGH SELF-REGULATION By David W. Sosnowski, M.S. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2019 Major Director: Wendy Kliewer, Ph.D. Professor of Psychology Department of Psychology The goals of present study were: (a) to examine associations between adverse childhood experiences (ACEs) and telomere length during childhood using ACE composite scores both with and without “new” adversities (i.e., parental death and poverty), and (b) to determine if ACEs indirectly affect telomere length through children’s self-regulatory abilities (i.e., effortful control and self-control). The analytic sample consisted of national data from teachers, biological parents, and their children (N = 2,527; Mage = 9.35, SD = .36 years; 52% male; 45% Black). Results from linear regression analyses revealed a statistically significant main effect of updated (but not traditional) ACEs on child telomere length, controlling for hypothesized covariates, although the additional amount of variance explained by ACEs was negligible. Results from mediation analyses revealed an indirect effect of ACEs on child telomere length through selfcontrol, assessed via a teacher-reported Social Skills Rating System, but not effortful control. While longitudinal studies are needed to strengthen claims of causation, the present study clarifies the association between ACEs and telomere length during middle childhood, and identifies a pathway from ACEs to changes in telomere length that should be explored further.
SemaSun: Visualization of Semantic Knowledge based on an improved Sunburst Visualization Metaphor

Ontologies have become an established data model for conceptualizing knowledge entities and describing semantic relationships between them. They are used to model the concepts of specific domains and are widespread in the areas of the semantic web, digital libraries and multimedia database management. To gain the most possible benefit from this data model, it is important to offer adequate visualizations, so that users can easily acquire the knowledge. Most ontology visualization techniques are based on hierarchical or graph-based visualization metaphors. This may result in information-loss, visual clutter, cognitive overload or context-loss. In this paper we describe a new approach of ontology visualization technique called SemaSun that is based on the sunburst visualization metaphor. We improved this metaphor, which is naturally designed for displaying hierarchical data, to the tasks of displaying multiple inheritance and semantic relations. This approach also offers incremental ontology exploring to reduce the cognitive load without losing the informational context.