Miracle-dz/UniFAR-FTUs huggingface dataset:
Basic Quantum Algorithms and Applications

Quantum computation, the ultimate goal of future computing, is an interesting field for researchers. The concept of quantum computation is based on basics of quantum mechanics. A quantum computer is a device for computation that makes direct use of quantum mechanical phenomena such as superposition and entanglement, to perform operations on data. The basic principle behind quantum computation is that quantum properties can be used to represent data and perform operations on these data. A quantum computer operates by manipulating the qubits with a fixed sequence of quantum logic gates. The sequence of gates to be applied is called a quantum algorithm. The field of quantum computation algorithm is fast moving and the scope is vast. Major quantum algorithms are summarized in this paper along with their applications. General Terms Quantum Algorithms.
The Tumor Necrosis Factor Superfamily Members TNFSF14 (LIGHT), Lymphotoxin β and Lymphotoxin β Receptor Interact to Regulate Intestinal Inflammation

Over 1.5 million individuals in the United States are afflicted with inflammatory bowel disease (IBD). While the progression of IBD is multifactorial, chronic, unresolved inflammation certainly plays a key role. Additionally, while multiple immune mediators have been shown to affect pathogenesis, a comprehensive understanding of disease progression is lacking. Previous work has demonstrated that a member of the TNF superfamily, TNFSF14 (LIGHT), which is pro-inflammatory in several contexts, surprisingly plays an important role in protection from inflammation in mouse models of colitis, with LIGHT deficient mice having more severe disease pathogenesis. However, LIGHT is a single member of a complex signaling network. It signals through multiple receptors, including herpes virus entry mediator (HVEM) and lymphotoxin beta receptor (LTβR); these two receptors in turn can bind to other ligands. It remains unknown which receptors and competing ligands can mediate or counteract the outcome of LIGHT-signaling during colitis. Here we demonstrate that LIGHT signaling through LTβR, rather than HVEM, plays a critical role in the progression of DSS-induced colitis, as LTβR deficient mice exhibit a more severe disease phenotype. Further, mice deficient in LTαβ do not exhibit differential colitis progression compared to WT mice. However, deletion of both LIGHT and LTαβ, but not deletion of both LTαβ and LTβR, resulted in a reversal of the adverse effects associated with the loss of LIGHT. In sum, the LIGHT/LTαβ/LTβR signaling network contributes to DSS colitis, but there may be additional receptors or indirect effects, and therefore, the relationships between these receptors and ligands remains enigmatic.
Audit of parenteral nutrition: standard parenteral nutrition regimens -feast or famine?

Background: Adequate nutrition of patients at a surgical unit is of great importance since both over- and undernutrition can lead to serious morbidity and even mortality. Surgical patients are frequently unable to meet nutritional needs by the enteral route and the use of SPN regimens is a common practice. Compared with patient-specific prescriptions, SPN solutions require fewer nutritional calculations, are less expensive, more convenient and offer greater biochemical stability. However, the accuracy and consistency with which these regimens meet patients? nutritional requirements remain unclear and are undefined in the literature. To examine whether patients at a surgical unit are adequately fed with SPN regimens, 13 surgical patients were prospectively followed- up and a comparison was made between the nutrients prescribed with the SPN solutions and the nutrients calculated individually for each patient. Mat erial and Methods: The exact amounts of macronutrients calculated and prescribed with the SPN regimens were collected. To calculate individualised nutritional requirement the Schofield equation was used with adjustment for activity and stress. Elia? s recommendation was used for protein requirements. Fat/carbohydrate calories were calculated. Anthropometry was used to estimate patients? nutritional status. Prescribed and calculated energy, nitrogen, fat and carbohydrate were compared using Wilcoxon signed rank tests. Spearman? s rho correlations were calculated. Results : Statistically significant difference was found between fat (sig.=0,001), carbohydrate (sig.=0,05) and energy (sig.=0,03) provided by SPN regimens and the ones calculated. No statistically significant difference was found between delivered and calculated nitrogen. ConclusionS: For short-term feeding, the potential benefits of SPN regimens may outweigh the risks associated with carbohydrate deficit and fat and energy excess. However, for longer-term feeding these risks may become clinically significant. Some improvement of the quality of feeding can be established by calculating nutritional requirements and by assessing the patients? nutritional status before commencing PN.
β‐ADRENOCEPTOR‐MEDIATED INHIBITION OF MEDIATOR RELEASE FROM HUMAN PERIPHERAL BLOOD‐DERIVED MAST CELLS

1 Mast cells cultured from human peripheral blood have been used as a cell model for functional studies of human mast cells, particularly human lung mast cells. However, the β‐adrenoceptor subtype expressed by these cultured cells has not been identified. The aim of the present study was to characterize pharmacologically the β‐adrenoceptors involved in the suppression of IgE‐mediated release of mediators, including histamine, prostaglandin (PG) D2 and leukotriene (LT) C4 from cultured mast cells. 2 Mast cells were cultured from mast cell progenitors isolated from peripheral blood in the presence of 200 ng/mL stem cell factor and 50 ng/mL interleukin‐6. Mast cells were sensitized with human myeloma IgE, treated with β‐adrenoceptor agonists or antagonist and then challenged with anti‐human IgE. The release of histamine, PGD2 and LTC4 from mast cells was determined. 3 Both isoprenaline and salbutamol inhibited anti‐IgE‐induced release of histamine, PGD2 and LTC4 from cultured mast cells in a dose‐dependent manner. Isoprenaline was a more potent inhibitor than salbutamol. The pD2 values for the inhibition of the release of histamine, PGD2 and LTC4 were 7.37 ± 0.12, 8.38 ± 0.23, 8.85 ± 0.23, respectively, for isoprenaline and 6.96 ± 0.12, 7.65 ± 0.36, 7.91 ± 0.64, respectively, for salbutamol. The selective β3‐adrenoceptor agonist BRL‐37344 failed to affect anti‐IgE‐induced histamine release from cultured mast cells. 4 The selective β2‐adrenoceptor antagonist ICI 118 551 (10−8 mol/L) strongly reversed the concentration‐dependent suppression of histamine release by isoprenaline and salbutamol; however, the selective β1‐adrenoceptor antagonist atenolol (10−6 mol/L) did not have any effect. 5 These results indicate that both isoprenaline and salbutamol act at β2‐adrenoceptors to suppress IgE‐mediated mediator release from cultured human mast cells.
A fast SAH-based construction of Octree

Recent GPU ray tracers can already achieve performance competitive to that of their CPU counterparts. Nevertheless, these systems can not yet fully exploit the capabilities of modern GPUs and can only handle medium-sized, static scenes. We present an octree construction algorithm for the GPU that achieves real-time performance by heavily exploiting the hardware, which has been observed to give superior performance in ray tracing compared to other acceleration structures. We use streaming construction with the surface area heuristic (SAH) that significantly increase the coherence of memory accesses during construction of the octree.
Low-quality fingerprint classification using deep neural network

Fingerprint recognition systems mainly use minutiae points information. As shown in many previous research works, fingerprint images do not always have good quality to be used by automatic fingerprint recognition systems. To tackle this challenge, in this work, the authors are focusing on very low-quality fingerprint images, which contain several well-known distortions such as dryness, wetness, physical damage, presence of dots, and blurriness. They develop an efficient, with high accuracy, deep neural network algorithm, which recognises such low-quality fingerprints. The experimental results have been obtained from the real low-quality fingerprint database, and the achieved results show the high performance and robustness of the introduced deep network technique. The VGG16-based deep network achieves the highest performance of 93% for dry and the lowest performance of 84% for blurred fingerprint classes.
Research in constraint-based layout, visualization, CAD, and related topics : a bibliographical survey

The present work compiles numerous papers in the area of computer-aided design, graphics, layout configuration, and user interfaces in general. There is nearly no conference on graphics, multimedia, and user interfaces that does not include a section on constraint-based graphics; on the other hand most conferences on constraint processing favour applications in graphics. This work of bibliographical pointers may serve as a basis for a detailed and comprehensive survey of this important and challenging field in the intersection of constraint processing and graphics. In order to reach this ambitious aim, and also to keep this study up-to-date, the authors appreciate any comment and update information.
Gamma-Band Correlations in Primary Visual Cortex

Neural field theory is used to quantitatively analyze the two-dimensional spatiotemporal correlation properties of gamma-band (30 - 70 Hz) oscillations evoked by stimuli arriving at the primary visual cortex (V1), and modulated by patchy connectivities that depend on orientation preference (OP). Correlation functions are derived analytically under different stimulus and measurement conditions. The predictions reproduce a range of published experimental results, including the existence of two-point oscillatory temporal cross-correlations with zero time-lag between neurons with similar OP, the influence of spatial separation of neurons on the strength of the correlations, and the effects of differing stimulus orientations. Graphical Abstract Highlights Incorporate orientation preference map into patchy connectivities of neurons in V1. Generalize spatiotemporal correlation function of neural activity to 2D spatially. Reproduce experimental results: synchronization of neural activities in gamma band. Temporal correlation between 2 measurements decreases with increasing separation. Predict 2D spatial map of temporal correlation strength between 2 measurement sites.
FOLLOW-UP STUDY OF FIVE HUNDRED PATIENTS WITH SCHIZOPHRENIA ADMITTED TO THE HOSPITAL FROM 1913 TO 1923

There are a number of studies on the outcome of schizophrenia, but few in which there has been an opportunity to view the material over a long span of years. In view of the enthusiasm for insulin and metrazol therapy, it would seem of advantage to have statistics on the outcome of schizophrenia in patients not treated by these methods. Late in 1936 a project was instituted at the Henry Phipps Psychatric Clinic for a study of the status of former patients. 1 The plan calls for a review of the 8,300 patients admitted to the clinic during its existence, with particular reference to scrutiny of the case material and study of the long term outcome. After preliminary organization of the material, contact with the patients was begun in 1937, twenty-four years after the first patient was admitted. During the two years that this project has been under way, repeated
Integrated semantic processing of complex pictures and spoken sentences - Evidence from event-related potentials

It has been suggested that semantic information processing is modularized according to the input form (e.g., visual, verbal, non-verbal sound). A great deal of research has concentrated on detecting a separate verbal module. Also, it has traditionally been assumed in linguistics that the meaning of a single clause is computed before integration to a wider context. Recent research has called these views into question. The present study explored whether it is reasonable to assume separate verbal and nonverbal semantic systems in the light of the evidence from event-related potentials (ERPs). The study also provided information on whether the context influences processing of a single clause before the local meaning is computed. The focus was on an ERP called N400. Its amplitude is assumed to reflect the effort required to integrate an item to the preceding context. For instance, if a word is anomalous in its context, it will elicit a larger N400. N400 has been observed in experiments using both verbal and nonverbal stimuli.
Legal and Ethical Considerations on Consent for Minors

About the Author: Christina Fogleman is a native of Olathe, Kansas. While at the KU School of Nursing she received a Clinical Excellence Award for her work in her Medical Surgical clinical courses and Honorable Mention for Clinical Excellence in the Foundations clinical course. She has accepted an invitation to join Delta Chapter – Sigma Theta Tau International, Nursing’s’ Honor Society. She will graduate with distinction in the top 10% of her class. After graduation she plans to begin her career on the Neuroscience Progressive Care Unit at The University of Kansas Hospital. Her long range plans include returning to school to pursue a masters or doctoral degree in nursing. She is also looking forward to using her nursing knowledge and ability to make a positive impact in the lives of her patients, co-workers, friends, and family. She wishes to acknowledge her faith in God for “giving me the talents I have”, along with her family and friends for “the support they continuously provide to me in order to succeed in my current endeavors”.
Human Face Detection in Color Image Based on C 4.5 Classifier

This paper present a new face detection algorithm based on human face feature. Method of YCbCr skin color space which is color segmentation of human face for regional analysis and extraction. Then we can use sobel edge detector to get edge which is boundaries between face regions and between face regions and image. Then we use convolution filter to remove noise.
The Models of Didactical Process Communicat?ons in Traditional and Distance Learning Systems: Analyses the State of the Art.

This paper consists of an analysis of the state of the art of research and development for the different models of didactical processes in traditional and distance learning systems. The educational system is an open and dynamic system. In such context as the educational system, seven models of didactical process communications can be observed. The contemporary models are based on collective knowledge building in collaborative learning environments. The last model needs self –regulated students’ competence of learning.
A contextual information retrieval framework

The amount of information on the Internet is constantly growing and the challenge now is one of finding relevant information. Contextual information retrieval (CIR) is a critical technology for today's search engines to facilitate queries and return relevant information. Despite its importance, little progress has been made in CIR due to the difficulty of capturing and representing contextual information about users. Numerous CIR approaches exist today, but, to the best of our knowledge, none of them offer a similar service to the one proposed in this paper. This paper proposes an alternative framework for CIR from the World Wide Web (WWW). The framework aims to improve query results (or make search results more relevant) by constructing a contextual profile based on a user's behaviour, their preferences, and a shared knowledge base, and by using this information in the search engine framework to find and return relevant information.
EVALUATION OF ADAPTIVE AND FIXED TIME TRAFFIC SIGNAL STRATEGIES: CASE STUDY OF SKOPJE

Signalized intersections and belonging signal plans are powerful means for effective urban traffic management. Numerous strategies have evolved over the time, from fixed time to intelligent signal plan control strategies that respond and react to traffic conditions in real time. This paper presents an evaluation and comparison of the impact of fixed time and UTOPIA adaptive traffic signal control strategies for the chosen urban corridor in the wider center area of the City of Skopje, Macedonia. A topic that still requires more attention from the research community. This paper presents a continuation of the author’s previous research where a framework to test UTOPIA adaptive control using the microscopic simulator VISSIM was described. Obtained new results include the influence of fixed time signal plans which are compared with UTOPIA’s results and analyzed in details using the following performance measures: delay, queue length, travel time, intersection level of service, number of stops and vehicle throughput.
Semantical analysis of higher-order abstract syntax

A choke-check valve for use as with a fluid motor to cushion the piston thereof as it approaches the end of its stroke characterized in that the valve has several modes of operation namely, one in which a choke adjusting member is operative to move a spring biased check valve member away from its seat to vary the flow capacity of the cushioning orifice through which fluid passes from the motor as the piston nears the end of its stroke without affecting the full flow characteristics of the check valve through which fluid passes into the motor to move the piston in the opposite direction; another in which the adjusting member moves toward the check valve seat while the check valve member is in seated position thus to define another adjustable cushioning orifice, again without affecting the pressure drop across the check valve when fluid flows into the motor; and yet another in which the adjusting member may be additionally moved toward the check valve seat to restrict fluid flow in both directions through the valve, even to the extent that fluid flow through the valve is stopped whereby the valve further constitutes a shut-off valve. The valve herein is further characterized in that the size or flow capacity of the cushioning orifice may be automatically varied as the piston decelerates during the cushioning portion of its stroke.
Susceptibility Test Methods: General Considerations

The main objective of susceptibility testing is to predict the outcome of treatment with the antimicrobial agents tested. The test results are generally reported to the treating physician, using the categories of susceptible, intermediate, and resistant. From the laboratory perspective, the key decisions involve the selection of a susceptibility testing method and the antimicrobial agents to be tested for each specimen and pathogen type. The principal methods used internationally are those of the Clinical and Laboratory Standards Institute (CLSI), based in the United States, and the European Committee on Antimicrobial Susceptibility Testing (EUCAST). Both organizations have a sophisticated approach to the setting of breakpoints (interpretive criteria) which permit the categorization of the susceptibility test results. This approach includes the collation and analysis of MIC distribution data, pharmacokinetic and pharmacodynamic data and associated target values, and clinical and bacteriological response rates from prospective clinical trials. This analysis is followed by the correlation of MICs and zone diameter distributions in order to establish breakpoints for commonly used methods. Modern susceptibility testing methods are often supplemented by specialized phenotypic and/or molecular testing to ensure that critical resistances and resistance mechanisms are detected.
DECISION TREE BASED CLASSIFICATION OF REMOTELY SENSED DATA

Over the last decade, many applications of neural network classifiers for land use classification have been reported in the literature, but few studies have assessed the use of decision tree classifiers. These latter techniques have substantial advantages for remote sensing classification problems due to their nonparametric nature, simplicity, robustness with respect to non-linear and noisy relations among input features and class labels, and their computational efficiency. A decision tree classifier has a simple form which can be compactly stored and that efficiently classifies new data. Decision tree classifiers can perform automatic feature selection and complexity reduction, while the tree structure gives easily understandable and interpretable information regarding the predictive or generalisation ability of the data. A decision tree recursively partitions a data set into smaller subdivisions on the basis of tests applied to one or more features at each node of the tree. In this study, a decision tree classifier is used for land use classification using Landsat-7 ETM+ data for an agricultural area near Littleport (Cambridgeshire), UK, for the year 2000. A field study was carried out to collect ground truth information about the various land use classes in the study area. Six land use classes (wheat, sugar beet, potatoes, peas, onions and lettuce) are selected for classification, and a univariate decision tree classifier is used for the labelling of the image pixels. The results of this study suggest that the decision tree classifier performs well, producing an overall accuracy of about 84.5%. The boosting technique, which improves the classification accuracy of a base classifier, was applied and the classification accuracy was increased by about 2 percent to 86.5%.
Gait deviations in children with cerebral palsy: a modeling approach

The gait pattern of children with cerebral palsy (CP) can be affected by many different underlying impairments, such as spasticity, contractures, weakness, and limited selective motor control. In combination with compensation strategies, that allow an optimal walking pattern despite these impairments, and considering the complex dynamics of human gait, it becomes difficult to determine the underlying causes of a specific gait deviation. Yet, a good understanding of these causes is essential in order to determine the best treatment for a patient. The aim of this thesis was to gain insight into the underlying causes of gait deviations; with a specific focus on the role of spasticity during gait, the interplay of spasticity with walking speed and muscle contractures, and possible dynamic causes of gait deviations.
COGNITIVE PROFILE OF SUBJECT 1 ABOUT PHILOSOPHY, PRINCIPLES ANDCHARACTERISTICS OF REALISTIC MATHEMATICS EDUCATION BEFORE AND AFTER STUDYING THE REALISTIC MATHEMATICS EDUCATION LEARNINGRESOURCE

The purpose of this study to create cognitive profiles of elementary school teachers who have been and have not been following the PMRI workshop, before and after they learning about the realistic mathematics education learning resource in understanding about philosophy, principles, and characteristics of realistic mathematics approach. The type of research used in this study is a combination of qualitative research and developmental research. The developmental research is used to construct a realistic mathematics education learning resource. The analysis steps of qualitative data which was built by Miles and Huberman (1994) is used to create cognitive profiles of teachers who become the subject research. The triangulation process of data used in this study is the triangulation of method. The results presented in this paper are the cognitive profile of one subject who is a PGSD student. Research subjects involved in the trial for the first task, the learning resource, and second task are six persons, which consists of three PGSD students who are working on the final project, and three elementary school teachers.