Miracle-dz/UniFAR-FTUs huggingface dataset:
Reactive Oxygen Species Mediated Prostaglandin E2 Contributes to Acute Response of Epithelial Injury

Reactive oxygen species (ROS) generated after tissue injury play a crucial role during wound healing through initiating acute inflammation, clarifying infection and dead tissue, and mediating various intracellular signal transduction. Prostaglandin E2 (PGE2) has been identified as one of the major factors responsible for inflammation and tissue repair. In this study, we tested our hypothesis that ROS produced by damaged human keratinocytes induces the synthesis of PGE2. In vitro epithelial wounding model was used to observe the production of ROS and secretion of PGE2 as well as the involved signal pathway. The mechanical injury caused the rapid production of ROS in in vitro cultured keratinocytes, which was significantly blocked by an inhibitor of nicotinamide adenine dinucleotide phosphate oxidase. The increased intracellular ROS caused by mechanical injury stimulates PGE2 production in a time-dependent manner via the activation of cyclooxygenase-2 (COX-2), which was stimulated by phosphorylation of extracellular signal-regulated protein kinase (ERK). These results indicate ROS-induced ERK activation leading to the activation of COX-2 and the synthesis of PGE2 in human keratinocytes responding to mechanical injury in the acute phase.
Effect of Rosehip (Rosa canina) Extracts on Human Brain Tumor Cell Proliferation and Apoptosis

Rosehips are blossoms from the wild rose (Rosa canina) and are commonly used as an herbal remedy. Previous reports have shown that extracts made from rosehip plants are able to reduce cell proliferation of cancer cells. In this study, we investigated the efficacy of rosehip extracts in preventing cell proliferation of three human glioblastoma cell lines A-172, U-251 MG and U-1242 MG cell lines. Each of the glioblastoma cell lines treated with rosehip extracts (1 mg/mL-25 ng/mL) demonstrated a significant decrease in cell proliferation. The rosehip extract-mediated decrease in cell proliferation was equal to or better than the decrease of cell proliferation observed when inhibitors of the MAPK (U0126, 10 μM) or AKT (LY294002, 20 μM) signaling pathways were utilized. Additionally, pretreatment of the these cell lines with Rosehip extracts (1 mg/mL-25 ng/mL) selectively decreased AKT, MAPK, and p70S6K phosphorylation suggesting these extracts prevent glioblastoma multiforme cell proliferation by blocking both the MAPK and AKT signaling mechanisms. Results from colorimetric cell death assays, cell cycle analysis by flow cytometry, as well as western blot studies demonstrate that rosehip extracts inhibit cell proliferation but do not promote apoptosis. Moreover, rosehip extracts were able to increase the efficacy of Temozolomide, a chemotherapeutic agent used to treat patients with glioblastomas. Surprisingly, rosehip extracts demonstrated a greater inhibition of cell proliferation than in combination with Temozolomide (100 μM) or Temozolomide as a single agent. Taken together these data suggest that rosehip extracts are capable of decreasing glioblastoma cell proliferation without promoting apoptosis and demonstrate a greater cell proliferation inhibitory effect than Temozolomide. More importantly, rosehip extracts may serve as an alternative or compliment to current chemotherapeutic regimens for glioblastomas.
Reducing the rate of post-surgical urinary tract infections in orthopedic patients

Urinary tract infection (UTI) is the fourth leading cause of healthcare-associated infections, with approximately 70%–80% being attributed to the inappropriate use of indwelling catheters. In many cases, indwelling catheters are used inappropriately without any valid indication, creating potentially avoidable and significant patient distress, discomfort, pain and activity restrictions, together with substantial care burden, cost and hospitalisation. In the Division of Orthopedic Surgery at Toronto Western Hospital (TWH), we identified UTI rate reduction as a quality improvement priority. Patients who underwent total hip and knee joint replacements and hip fracture repairs at TWH were monitored for the incidence of UTI and the usage of catheters. The data collected as part of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) revealed UTI rate of 2.1% among 666 patients who were treated between January and June 2016. Data collected through a custom field in the ACS NSQIP workstation further revealed that indwelling catheters were overused, with 55.2% of patients receiving indwelling catheters in the same time period. These data were presented to the orthopaedic leadership group and surgeons at TWH in July 2016 to set the quality improvement target and create the working group. Nursing staff was provided education to strictly follow the institutional catheter-associated UTI prevention guidelines and change ideas based on the guidelines were implemented in July 2016. As a result, the rate of UTI decreased to 1.1% and the use of indwelling catheter decreased to 19.8% among 883 patients who were treated between July 2016 and March 2017. The study indicated that a systematic approach, engaging all front-line staff including nurse educators and nurse practitioners, helps to facilitate implementation of practice changes. We expect that ongoing reminders and education ensure that the changes are sustainable.
Feedback-aided coded caching for the MISO BC with small caches

This work explores coded caching in the symmetric K-user cache-aided MISO BC with imperfect CSIT-type feedback, for the specific case where the cache size is much smaller than the library size. Building on the recently explored synergy between caching and delayed-CSIT, and building on the tradeoff between caching and CSIT quality, the work proposes new schemes that boost the impact of small caches, focusing on the case where the cumulative cache size is smaller than the library size. This small-cache setting places an additional challenge due to the fact that some of the library content must remain entirely uncached, which forces us to dynamically change the caching redundancy to compensate for this. Our proposed scheme is near-optimal, and the work identifies the optimal cache-aided degrees-of-freedom (DoF) performance within a factor of 4.
Management towards reducing cloud usage costs

Many organizations are attracted to cloud computing as an ICT (information and communications technology) sourcing model that can improve flexibility and total cost of ICT systems. However, it can be difficult for a prospective cloud customer to determine and manage cloud usage costs. We present an overview of several NICTA research projects that aim at providing information that can help ICT professionals determine various cloud usage costs and make decisions that are appropriate from the business viewpoint. Before migrating an application into a cloud, it is necessary to choose to which cloud to migrate, because there is a huge variety of cloud offerings, with significantly different pricing models. To accurately capture projected operating costs of an application in a particular cloud and enable side-by-side comparison of cloud offerings from different providers, NICTA developed a cost estimation tool that calculates the costs based on usage patterns and other characteristics of the application. This tool can also be used during runtime as an input into making adaptation/control decisions. To collect various runtime metrics (e.g., about the amount of transferred data or received quality of service - QoS) that are necessary for operational management and assessment of cloud usage costs, NICTA developed an innovative tool for flexible and integrated monitoring of applications in clouds and (in case of hybrid clouds) related local data centers. To help determine which runtime adaptation/control decisions are best from the business viewpoint (e.g., incur lowest cost), we extended the WS-Policy4MASC language and MiniZnMASC middleware for autonomic business-driven IT management with events and adaptation actions relevant for cloud management. The tools from the presented projects can be used separately or as parts of a powerful integrated cloud management system (which contains several additional tools).
How Reform Worked in China

China’s reform worked and produced some of the most impressive growth in the largest developing and transition economy in the world in the past twenty-two years. That China has managed to grow so rapidly despite the absence of many conventional institutions such as rule of law and secure private property rights is puzzling. To understand how reform works in a developing and transition economy that has great growth potential, it is not enough to study the conventional ‘best-practice institutions’ as a desirable goal. One should also study how feasible, imperfect institutions have evolved to complement the initial conditions and to function as stepping stones in the transition toward the goal. Underlying China’s reform is a serial of institutional changes concerning the market, firms, and the government in the novel form of ‘transitional institutions. ’ These institutions succeed when they achieve two objectives at the same time: to improve economic efficiency by unleashing the standard forces of incentives and competition on the one hand, and to make the reform a win-win game and thus interest compatible for those in power on the other.
Why Do Women Want Children? The Case of Hong Kong, China: A Lowest-Low Fertility Context

ABSTRACT Governments in low fertility countries tend to tackle low birth rates by addressing macro-level factors rather than the meaning that having a child holds for men and women. Yet whether or not an individual decides to have a child depends in part on what they think having a child will mean for their lives. This study examines the meanings that constitute reasons for wanting a child among a sample of middle-class, married, Hong Kong Chinese women who wanted children. These women were living in Hong Kong when it had one of the lowest total fertility rates in the world and the lowest in its history. Using semi-structured, in-depth interviews, it finds that for these women, to have a child makes one’s family complete; is the next stage of life; provides happiness, fun, and enjoyment; brings care and company in old age; and children are “lovely” and “cute. ” Governments concerned about low birth rates can use research on what having a child means for women to improve policy so as to make having a child more attractive, and to create messages that hold greater appeal to women.
Usage Profile Rating of Suitability to E-Vehicles Utilizing a Physical Consumption Model

The project “Wohnungswirtschaftlich integrierte netzneutrale Elektromobilitat in Quartier und Region” (WINNER) aims to integrate shared electric vehicles, smart local grids and renewable energy in tenant households. This paper focuses on how to find the model of an electric vehicle (consumption, recharging, usage) which perfectly matches the requirements of particular carsharing stations. This approach utilizes usage profiles of conventional combustion vehicles. Each profile describes booking time and distance. Applying that information to a rating model which simulates the driving task and charges the vehicle between usages should be able to tell how much bookings might be handled by an electric vehicle. Within this paper, we give an introduction to our simulation system. This covers the data model, transforming bookings into driving tasks, and the consumption and charging model itself. Further, we validate the model by using high detailed data captured on regular routes as well as booking sets with electric vehicles. This validation shows an average relative error of 10% for high detailed data from and an average relative error for booking information with known consumptions of 5%. Finally, we present the application of our simulation system to make a decision based on historical booking information. This application example shows that 90% usages at some station might be handled with electric vehicles, while others should not be replaced.
Evolving core promoter signal motifs

DNA annotation is an important problem in molecular biology. The task in annotation is to determine functional roles of DNA regions. We are interested in core promoter regions in eukaryotes; these are approximately 50 bp in length, and are believed to act as the critical factor in attracting the transcription initiation complex to the DNA at that site, so promoting the transcription of a gene immediately downstream. The pattern of nucleotides which constitute a core promoter region is very complex, resulting in relatively poor performance from classification methods so far in terms of distinguishing true core promoter regions from other regions of DNA. The methods described both use evolutionary algorithms to optimise simple models of core promoter regions. They seem to perform comparably to the best of many published methods so far, but has the advantage of simplicity and transparency. That is, we are able to evolve easily understandable models of the core promoter region which perform comparably with the best of existing techniques. There seem to be several ways in which the scheme can be further developed.
MDCT domain postfiltering for speech quality enhancement

In this paper, we propose a MDCT domain postfilter to suppress the noise in speech spectral valleys and allow more noise in speech spectral peaks. Since peaks and valleys of MDCT coefficients don't correspond to those of speech spectrum, we construct both the short-term and long-term postfilter using MDCT pseudo spectrum. The short-term postfilter is induced by smoothing the envelope that is obtained by a piece-wise linear interpolation between consecutive local minima of the MDCT pseudo spectrum. And the long-term postfilter is generated by smoothing the residual spectrum that is a difference between the MDCT pseudo spectrum and envelope. Experiments show that the proposed method outperforms the G.729. 1 postfilter.
Gait Recognition Based on Structural Gait Energy Image

Gait energy image (GEI) has been proven to be an effective gait recognition feature. It has good performance on most of public databases. However, GEI ignores most of gait motion information and doesn’t contain enough human body structure information neither, which negatively affect its robustness in varying clothing and carrying conditions. We propose a new gait recognition method called structural gait energy image (SGEI), which combines the advantages of GEI and model-based methods. SGEI is generated by a fusion of foot energy image (FEI) and head energy image (HEI). A classifier fusion of GEI and SGEI is then conducted. Our method can cope with the clothing and carrying variations pretty well. We test it on CASIA(B) database and get a recognition rate of 89.29%, which is much higher than GEI whose recognition rate is 60.37% only.
conga: A Framework for Adaptive Conducting Gesture Analysis

Designing a conducting gesture analysis system for public spaces poses unique challenges. We present conga, a software framework that enables automatic recognition and interpretation of conducting gestures. conga is able to recognize multiple types of gestures with varying levels of difficulty for the user to perform, from a standard four-beat pattern, to simplified up-down conducting movements, to no pattern at all. conga provides an extendable library of feature detectors linked together into a directed acyclic graph; these graphs represent the various conducting patterns as gesture profiles. At run-time, conga searches for the best profile to match a user's gestures in real-time, and uses a beat prediction algorithm to provide results at the sub-beat level, in addition to output values such as tempo, gesture size, and the gesture's geometric center. Unlike some previous approaches, conga does not need to be trained with sample data before use. Our preliminary user tests show that conga has a beat recognition rate of over 90%. conga is deployed as the gesture recognition system for Maestro! , an interactive conducting exhibit that opened in the Betty Brinn Children's Museum in Milwaukee, USA in March 2006.
Optimum power allocation for Amplify-and-Forward cooperation strategy in WSN

Energy is an extremely limited resource in wireless sensor networks (WSNs). Thereby, various power management strategies have been proposed to reduce the quantity of consumed energy. In this article, the aim of our approach is to provide the optimal transmission power in order to maximize the network lifetime using the orthogonal channels and taking into account a Symbol Error Rate (SER) constraint at the Fusion Center (FC). In order to analyze our approach, we will first study the case where the information passes by a single relay to reach the destination creating several boughs. We call this case “virtual mimo with a single relay”. Second, we will consider a specific case with a single bough and several relays and then generalize a global case with several relays and several boughs. In addition, we suppose that a Maximum Ratio Combining (MRC) is used by the receiver as a detector, and Amplify and Forward (AF) is used as a relaying strategy where the channel gain coefficients are known. Simulation results show the viability of our approach.
Decollectivist Strategies in Oceania

Each action of a decollectivizing employer—be it in the realm of employment practices, information or relational actions—has both real and symbolic dimensions that may be inclusivist, exclusivist or both. While many attempts at decollectivism are crude, Australia has seen the emergence of a coherent model of sophisticated decollectivist behaviour which has policy implications for many countries. Some analogies can be seen between certain sophisticated strategies of decollectivizing employers and state strategies of Oceania in Orwell’s 1984, though there are many limits to such analogies and indeed to the success of decollectivist strategies, due to the contradiction between rhetoric and actions, employees’ exposure to other discourses and the potential for union response and renewal.
PyPLN: a Distributed Platform for Natural Language Processing

This paper presents a distributed platform for Natural Language Processing called PyPLN. PyPLN leverages a vast array of NLP and text processing open source tools, managing the distribution of the workload on a variety of configurations: from a single server to a cluster of linux servers. PyPLN is developed using Python 2.7. 3 but makes it very easy to incorporate other softwares for specific tasks as long as a linux version is available. PyPLN facilitates analyses both at document and corpus level, simplifying management and publication of corpora and analytical results through an easy to use web interface. In the current (beta) release, it supports English and Portuguese languages with support to other languages planned for future releases. To support the Portuguese language PyPLN uses the PALAVRAS parser\citep{Bick2000}. Currently PyPLN offers the following features: Text extraction with encoding normalization (to UTF-8), part-of-speech tagging, token frequency, semantic annotation, n-gram extraction, word and sentence repertoire, and full-text search across corpora. The platform is licensed as GPL-v3.
HIV Disease, Antiretroviral Therapy Safety and the Cardiovascular System. Clinical-Instrumental Assessment of Antiretroviral-Naïve Versus Subjects Already Treated with Antiretroviral Agents

Background: There is controversy over whether or not HIV infection and antiretroviral therapy contribute to early atherosclerosis. Ultrasonographic evaluation of carotid intima-media thickness is considered as a reliable surrogate marker of subclinical atherosclerosis and may be employed in the setting of a cardiovascular risk assessment in HIV- infected patients. Patients and methods: A cross-sectional study evaluating classical risk factors for cardiovascular diseases, parameters of HIV infection, antiretroviral therapy and subclinical atherosclerosis in HIV-positive subjects naive or treated with antiret- roviral agents was performed. The enrolled patients underwent ultrasonography of the epi-aortic vessels using a Philips HDI 5000 power color-Doppler with 7.5-MHz probes. The 10-year risk of coronary heart disease was calculated by the Framingham equation. Results: A total of 27 patients (19 males and 8 females; mean age 44 + 13 years; range 32-59 years) was enrolled in the study: 11 subjects were naive to all antiretroviral agents (group A) and 16 patients were treated with antiretroviral therapy for >36 months (group B). Mean duration of known HIV infection was significantly longer in group B than in group A, such as frequency of dyslipidemia and lipodystrophy syndrome. Prevalence of carotid plaques was significantly higher in group B than in group A (43.7% versus 0; p=0.012). In group B, patients with intermediate to high 10-year risk of coro- nary heart disease (>10%) showed a significantly higher intima-media thickness and prevalence of carotid lesions than those with low risk (<10%). Moreover, carotid plaques presented structural features comparable to those of classical athe- rosclerotic plaques observed in general population, with iso-hyperechonegic aspects and irregular surfaces. Conclusions: Prevalence of carotid atherosclerosis is higher in HIV-infected patients previously treated with antiretrovi- rals than in those naive to antiretroviral therapy and seems mostly associated with a longer duration of HIV infection, more severe lipid metabolism alterations, presence of lipodystrophy syndrome, and a more elevated 10-year risk of car- diovascular diseases.
Perspectives on combining model-driven engineering, software product line engineering, and version control

Model-driven software engineering (MDSE), software product line engineering (SPLE), and version control (VC) have been established as three software engineering sub-disciplines dealing with raising the level of abstraction of software development, organizing variability in a systematic way, and controlling the evolution of software artifacts, respectively. Traditionally, these sub-disciplines are supported by disjoint tools, leading to undesirable context switches. In this tool-centric survey, approaches for combining MDSE, SPLE, and VC in a pair-wise or even holistic fashion are categorized and assessed. The combination of MDSE and SPLE is natural since models are used to describe both the problem and the solution space. Moreover, specific VC support for models may improve collaborative MDSE in a similar way as dedicated SPL versioning supports evolution control. Last, both VC and SPLE deal with different types of variability - in time and in space, respectively -, such that an integration promises to close the gap between historical and logical (model) versioning. Results indicate that these promises are only satisfied partly by existing approaches. To attest this, we conclude with a list of usage scenarios for combined MDSE/SPLE/VC that cannot be adequately addressed by the current tools.