Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Significance of Keap1 and Nrf2 in Oral Squamous Cell Carcinoma

Oxidative stress has been reported to play an important role in progression and prognostication in various kinds of cancers. However, the role and clinical significance of oxidative stress markers Keap1 and Nrf2 in oral squamous cell carcinoma (OSCC) has not been elucidated. This study aimed to investigate the correlation of oxidative stress markers Keap1 and Nrf2 expression and pathological features in OSCC by using tissue microarray. Tissue microarrays containing 17 normal oral mucosa, 7 oral epithelial dysplasia and 43 OSCC specimens were studied by immunohistochemistry. The association among these proteins and pathological features were analyzed. Expression of oxidative stress markers Keap1, Nrf2, and antioxidants PPIA, Prdx6, as well as CD147 was found to increase consecutively from normal oral mucosa to OSCC, and the Keap1, Nrf2, PPIA, Prdx6, CD147 expression in OSCC were significantly higher when compared to normal oral mucosa. Expression of Keap1, Nrf2 in tumors was not found to be significantly associated with T category, lymph node metastases, and pathological grade. Furthermore, we checked the relationship among these oxidative stress markers and found that Keap1 was significantly correlated with Nrf2, Prdx6 and CD147. Significant relationship between Nrf2 and Prdx6 was also detected. Finally, we found patients with overexpression of Keap1 and Nrf2 had not significantly worse overall survival by Kaplan–Meier analysis. These findings suggest that ROS markers are associated with carcinogenesis and progression of OSCC, which may have prognostic value and could be regarded as potential therapeutic targets in OSCC.
Parsing with subdomain instance weighting from raw corpora

The treebanks that are used for training statistical parsers consist of hand-parsed sentences from a single source/domain like newspaper text. However, newspaper text concerns different subdomains of language use (e.g. finance, sports, politics, music), which implies that the statistics gathered by generative statistical parsers are averages over subdomain statistics. In this paper we explore a method, subdomain instance-weighting, that exploits raw subdomain corpora for introducing subdomain statistics into a state-of-the-art generative parser. We employ instance-weighting for creating an ensemble of subdomain specific versions of the parser, and explore methods for amalgamating their predictions. Our experiments show that subdomain statistics extracted from raw corpora can even improve the quality of the n-best lists of a formidable, state-of-the-art parser.
Fuzzy Array Dataflow Analysis

Dataflow analyses track the definitions and uses of variable values and are useful for optimizing and parallelizing compilers. Such analyses compute, for every (array cell) value read in a right-hand-side expression, the very operation which produced it. These analyses, however, require quite stringent hypotheses on the input programs: the control flow should be known at compile-time (i.e., static), and array subscripts must be affine functions of surrounding counters and possibly of symbolic constants. In contrast, the analysis presented in this paper handles generalifs andwhileloops and general nonaffine array subscripts.
Experimental Studies in Rats on the Effects on Growth and Intestinal Microflora of a New Mix Combining Calcium, Iron, Zinc and a Prebiotic in a Milk-like Vehicle

The aim of this work was to determine the effects of a new mineral mix combined with a prebiotic on growth, mineral deposit and intestinal microflora using a milk-like vehicle. This study was performed with Sprague Dawley female rats separated into 7 groups. Group 1 was fed with a deficient diet on its mineral content, group 2, 3 and 4 were fed with normal diets on their mineral content during 28 days but group 2 was fed with a diet containing reference Ca, Fe and Zn sources and groups 3 and 4 with diets containing other Ca, Fe and Zn sources that were evaluated. Group 4 received additionally a diet containing a prebiotic. Groups 5, 6 and 7 were submitted to a depletion period of 14 days during which they were fed as group 1 and then to a repletion period of 14 days when they were fed with the same diets as group 2, 3 and 4 respectively. Initial and final body weight, average growth rate, liver and femur weight, iron and zinc liver content as well as calcium and zinc femur content were the parameters evaluated for the growth and mineral deposit analysis. An- aerobes, enterobacteria, lactobacilli and bifidobacteria recount was performed from feces samples collected on different treatment days. Mineral sources under study presented slightly better characteristics than the reference standard ones. Moreover, the combination with a prebiotic may produce some advantages related to mineral absorption and intestinal microflora composition as a bifidogenic effect was confirmed.
Hedging Cloud Energy Costs via Risk-free Provision Point Contracts

The cost of electricity is a major concern to public providers of cloud computing services. On-demand pricing, common amongst cloud providers, does not aid the provider in planning future demand and therefore purchasing energy at discounted rates. In this paper, we describe a number of advance pricing schemes for cloud computing resources based on provision-point contracts, commonly used by deal-of-theday websites such as Groupon. We propose three models – Group Provision Points, Contributory Provision Points, and Variable Reward Forwards – that each reward consumers with reduced prices for advance reservations, while allowing providers to make accurate forecasts of energy usage. Furthermore, we show how the schemes are risk-free for the provider, guaranteeing to be at least as profitable as on-demand schemes. We present results from a simulation of the schemes, and compare the results to our analytically derived predictions.
A Phase I Trial of the HIV Protease Inhibitor Nelfinavir with Concurrent Chemoradiotherapy for Unresectable Stage IIIA/IIIB Non-small Cell Lung Cancer: A Report of Toxicities and Clinical Response

Background: The objective of this phase I trial was to determine dose-limiting toxicities (DLT) and the maximally tolerated dose of the radiosensitizer Nelfinavir in combination with concurrent chemoradiotherapy in locally advanced non-small cell lung cancer (NSCLC). Methods: Nelfinavir (dose level 1: 625 mg orally [PO] twice a day; dose level 2: 1250 mg PO twice a day) was administered for 7 to 14 days before and concurrently with concurrent chemoradiotherapy to patients with biopsy confirmed IIIA or IIIB unresectable NSCLC. Five patients were treated at dose level 1; eight patients were treated at dose level 2. Patients were treated with concurrent chemoradiotherapy to a dose of 66.6 Gy. DLTs were defined as any treatment-related grade 4 hematologic toxicity requiring a break in therapy or nonhematologic grade 3 or higher toxicity except esophagitis and pneumonitis. Results: Sixteen patients were enrolled and 13 patients received at least one dose of nelfinavir. Twelve patients were treated with nelfinavir and concurrent chemoradiotherapy. No DLTs have been observed at either dose level. The maximum tolerated dose of nelfinavir was therefore 1250 mg PO twice a day. Six patients experienced grade 4 leukopenia. One patient experienced grade 4 thromobcytopenia. Median follow-up for all 12 response-evaluable patients was 31.6 months and for survivors is 23.5 months. Nine of the 12 patients had evaluable posttreatment positron emission tomography/computed tomography with metabolic response as follows: overall response: 9/9 (100%); complete response: 5/9 (56%); and partial response: 4/9 (44%). Conclusion: Nelfinavir administered with concurrent chemoradiotherapy is associated with acceptable toxicity in stage IIIA/IIIB NSCLC. The metabolic response and tumor response data suggest that nelfinavir has promising activity in this disease.
Exploiting Task Relatedness to Learn Multiple Bayesian Network Structures

We address the problem of learning multiple Bayesian network structures for experimental data where the experimental conditions define relationships among datasets. A metric of the relatedness of datasets, or tasks, can be described which contains valuable information that we exploit to learn more robust structures for each task. We represent the task-relatedness with an undirected graph. Our method uses a regularization framework over this task-relatedness graph to learn Bayesian network structures for each task that are smoothed toward the structures of related tasks. Experiments on synthetic data and real fMRI experiment data show that this method learns structures which are close to ground truth, when available, and which generalize to holdout data better than an existing multitask learning method, learning networks independently, and learning one global network for all tasks.
Gait assessment in Parkinson's disease: toward an ambulatory system for long-term monitoring

An ambulatory gait analysis method using body-attached gyroscopes to estimate spatio-temporal parameters of gait has been proposed and validated against a reference system for normal and pathologic gait. Later, ten Parkinson's disease (PD) patients with subthalamic nucleus deep brain stimulation (STN-DBS) implantation participated in gait measurements using our device. They walked one to three times on a 20-m walkway. Patients did the test twice: once STN-DBS was ON and once 180 min after turning it OFF. A group of ten age-matched normal subjects were also measured as controls. For each gait cycle, spatio-temporal parameters such as stride length (SL), stride velocity (SV), stance (ST), double support (DS), and gait cycle time (GC) were calculated. We found that PD patients had significantly different gait parameters comparing to controls. They had 52% less SV, 60% less SL, and 40% longer GC. Also they had significantly longer ST and DS (11% and 59% more, respectively) than controls. STN-DBS significantly improved gait parameters. During the stim ON period, PD patients had 31% faster SV, 26% longer SL, 6% shorter ST, and 26% shorter DS. GC, however, was not significantly different. Some of the gait parameters had high correlation with Unified Parkinson's Disease Rating Scale (UPDRS) subscores including SL with a significant correlation (r=-0.90) with UPDRS gait subscore. We concluded that our method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.
Learning as the construction of a new reality

Within a concept of life‐long learning, the study here reported is framed within the context of the expanding use of education and training in achieving organisational change. The focus of the research study was on one particular organisational education and training intervention and on how individuals experienced the learning and implementing of part of that intervention, namely group process facilitation. Such experiences may best be understood from the perspective of the learners themselves. There were four important factors reported that impinged on the learning process for the participants and that helped them construct new realities: the novelty of the learning environment; the value of flexibility; the value of openness; and the educational value of difference.
Ratings of L‐DOPA‐Induced Dyskinesia in the Unilateral 6‐OHDA Lesion Model of Parkinson's Disease in Rats and Mice

This unit provides detailed protocols for establishing rodent models of L‐DOPA‐induced dyskinesia. The 6‐hydroxydopamine (6‐OHDA) lesion procedure is described in more detail for mice than for rats since the lesioning procedure in rats has been described extensively in previous work and is less difficult to perform. Unlike primate models, rodent models of L‐DOPA‐induced dyskinesia are relatively simple and fast to set up, thus being affordable to most laboratories. These models allow for studying the dyskinetic complications of L‐DOPA treatment on large groups of animals under strictly controlled experimental conditions. Along with information and structured protocols for the practical execution of the test, this unit provides a detailed description of the rating scale and the phenomenology of rodent abnormal involuntary movements, and suggestions for beginners. Curr. Protoc. Neurosci. 41:9.25. 1‐9.25. 23. © 2007 by John Wiley & Sons, Inc.
Behavioral Engagement in Learning and Math Achievement over Kindergarten: A Contextual Analysis

Using nationally representative data on 12,462 kindergarten children, this report examines the link between behavioral engagement and math achievement growth during kindergarten. Multilevel models show that students with higher individual engagement tend to experience larger math achievement growth over kindergarten, that classroom engagement makes a difference in how much achievement growth students experience over kindergarten, and that students with higher individual engagement benefit more from being in highly-engaged classrooms than children with lower individual engagement. Students with higher math test scores at kindergarten entry also benefit more from highly-engaged classrooms than children with lower prior math scores. Results from this study provide new evidence that behavioral engagement affects students’ achievement growth on multiple levels, with the individual, the classroom environment, and the interaction of the individual and classroom environment all relating to math outcomes. Evidence reported from this study is central to reducing educational inequalities.
Naming and branding: accountants and accountancy bodies in the British Empire and Commonwealth, 1853-2003

The number of professional accountancy bodies and accountants within the countries of the British Empire and Commonwealth has greatly expanded within the last 150 years. Each body has had to choose a name for itself. This paper attempts to explain these names and the designations of the members. The names and designations are argued to be exclusionary and inclusionary devices that in many cases have been appropriated from other countries, notably the UK and the US. Certain designations, notably “chartered accountant” and “CPA”, have evolved as brand names. It is argued that access to and use of these brands has spread not with colonisation but with the decolonisation of, first, the settler colonies and then the non-settler colonies. The paper discusses the choice between “chartered” and “CPA” and why neither has become the brand of international accountancy firms operating within a global economy.
Analysing Security Protocols with AVISPA

Usage of the Internet has increased rapidly over the past decade. Increased amount of network users has also brought along a need of network-based services that require security. Developing new security protocols is a difficult task and sometimes too difficult task for human mind. We need an efficient tools to help the development and verification of the protocols. In this paper we introduce the protocol analysis tool called AVISPA. The paper describes the architecture of the tool and syntax for protocol specification language called HLPSL. We give an example of how a real protocol can be specified with the HLPSL language and how the output of the AVISPA Tool is analysed.
A Case for Addressing Privacy Problems with Technical , not Legislative , Solutions

Free online services have become an indelible part of today’s Internet usage experience. The online experience of many users centers around web search (Google, Bing), web-based email (Gmail, Hotmail), online social networks (Facebook, MySpace), and video sharing (YouTube). Each of these services demand that users share their personal or usage information to some extent. Web-based email providers like Gmail, for example, require the ability to read users’ emails so that they may target advertisements based on an email’s contents. Ostensibly, other reasons for which services wish to have access to user data include simply making the service better, debugging and maintaining the service, or personalizing the user experience. Unfortunately, users are often unaware that they are making their private information available to a company they have no compelling reason to trust. Further, many important questions remain unclear at best: Once a user uploads their data, who owns it? What does the service do with that data? What steps does the service take to ensure the confidentiality and availability of the data? We believe that user privacy is paramount in today’s Internet. Provable privacy is not only good for users of a service, it is good for the service itself. For instance, if a service never stores users’ information unencrypted, then that service is indemnified from attacks on their own infrastructure. After all, even the most earnest security policies can be undermined by those who have physical access to the machines storing the data, such as disgruntled or careless employees. Maintaining user privacy also opens opportunities for more to use the service than could before. For example, many universities cannot move their email service to a web-based system due to privacy policy restrictions, even though doing so could lead to extensive savings. Were email providers to en­ sure the provable privacy of the colleges’ data, this roadblock would be removed and web-mail providers might profit from ads targeted to the new customers [4].
ScienceDirect International Conference on Accounting Studies 2014 , ICAS 2014 , 18-19 August 2014 , Kuala Lumpur , Malaysia Corporate voluntary disclosure practices of banks in Bangladesh

This study aims to explore the corporate voluntary disclosure practices of the listed banks in an emerging economy namely Bangladesh. Results show that the extent of voluntary disclosure significantly improves from 2005 to 2008. However, the level of disclosure items related to corporate governance and risk management are lower than other disclosure categories. Overall findings of this study contribute in the accounting and economic literature by adding an empirical results of voluntary disclosure of a highly regulated industry from an emerging economy. Nevertheless, the results have the limitation to generalize for other industries as well as for banks from countries. © 2014 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the School of Accountancy, College of Business, Universiti Utara Malaysia.
Computational Study of Stylistics: A Clustering-Based Interestingness Measure for Extracting Relevant Syntactic Patterns

In this contribution, we present a computational stylistic study of the French classic literature texts based on a data-driven approach where discovering interesting linguistic patterns is done without any prior knowledge. We propose an objective interestingness measure to extract meaningful stylistic syntactic patterns from a given author’s work. Our hypothesis is based on the fact that the most characterising linguistic patterns should significantly reflect the author’s stylistic choice in that the positions of theirs occurrences are controlled by the author’s purpose, while the irrelevant linguistic patterns are distributed randomly in the text. Since it does not rely on the counts of occurrences of the syntactic patterns in texts, this measure can work reasonably well with both large and small text samples. The analysed results show the effectiveness in extracting interesting syntactic patterns from a single text, and this seems particularly promising for the analyses of such texts that, for their characteristics or for historical reasons, cannot support a comparative study.
HierarchyMap: A Novel Approach to Treemap Visualization of Hierarchical Data

The HierarchyMap describes a novel approach for Treemap Visualization method for representing large volume of hierarchical information on a 2-dimensional space. HierarchyMap algorithm is a new ordered treemap algorithm. Results of the implementation of HierarchyMap treemap algorithm show that it is capable of representing several thousands of hierarchical data on 2-dimensional space on a computer and Portable Device Application (PDA) screens while still maintaining the qualities found in existing treemap algorithms such as readability, low aspect ratio, reduced run time, and reduced number of thin rectangles. The HierarchyMap treemap algorithm is implemented in Java programming language and tested with dataset of Departmental and Faculty systems of Universities, Family trees, Plant and Animal taxonomy structures
Dynamic surface control for a class of nonlinear systems

A method is proposed for designing controllers with arbitrarily small tracking error for uncertain, mismatched nonlinear systems in the strict feedback form. This method is another "synthetic input technique," similar to backstepping and multiple surface control methods, but with an important addition, /spl tau/-1 low pass filters are included in the design where /spl tau/ is the relative degree of the output to be controlled. It is shown that these low pass filters allow a design where the model is not differentiated, thus ending the complexity arising due to the "explosion of terms" that has made other methods difficult to implement in practice. The backstepping approach, while suffering from the problem of "explosion of terms" guarantees boundedness of tracking errors globally; however, the proposed approach, while being simpler to implement, can only guarantee boundedness of tracking error semiglobally, when the nonlinearities in the system are non-Lipschitz.
English as a Second Language in South Africa's Tertiary Institutions: A Case Study at the University of Pretoria.

This paper uses the University of Pretoria as a point of reference and explicates that the use of a second language as language of learning and teaching (LoL/T) could be detrimental to the academic development of students as well as to the assessment of their progress, if the students concerned do not have the expected proficiency in the LoL/T, which, in the case of the University of Pretoria, is English. The argument is motivated on the basis of the role of language in academic training and on the proficiency of the students concerned in English. The article then lists the language and language-related problems at the University of Pretoria, evaluates the measures taken by the University to resolve these problems, and closes with a description of the language planning steps which are necessary if the language issue at the University is to be handled in a satisfactory way. Although directed at circumstances at one particular South African university it is hoped that the discussion may be applicable to similar institutions in the country, in particular institutions which formerly wholly or mainly used Afrikaans as LoL/T, and have had to adopt a dual-medium approach to training since the country's democratisation in 1994.
Distributed genetic resampling particle filter

Particle filter (PF) is one of the most important nonlinear filtering methods and has received much attention from many fields over the past decade, but the degeneracy phenomenon and large computation amount of PF have significant negative impacts on its filtering accuracy and real-time performance. In order to solve the problems of PF, this paper integrates distributed genetic algorithms (DGAs) and PF, and puts forward the distributed genetic resampling particle filter (DGRPF). This method divides all particles into several subpopulations to parallel execute particle filtering. Several genetic operators such as crossover, mutation, selection and migration are adopted to optimize the resampling process, which can effectively suppress degeneracy phenomenon, increase particles diversity, and make PF easy to execute in the distributed processor. By software simulation, DGRPF is compared with several existed PF algorithms in the tracking performance, estimation accuracy and computation efficiency, and the effectiveness of DGRPF has been verified.