Miracle-dz/UniFAR-FTUs huggingface dataset:
Cluster Content Caching: An Energy-Efficient Approach to Improve Quality of Service in Cloud Radio Access Networks

In cloud radio access networks (C-RANs), a substantial amount of data must be exchanged in both backhaul and fronthaul links, which causes high power consumption and poor quality of service (QoS) experience for real-time services. To solve this problem, a cluster content caching structure is proposed in this paper, which takes full advantages of distributed caching and centralized signal processing. In particular, redundant traffic on the backhaul can be reduced because the cluster content cache provides a part of required content objects for remote radio heads (RRHs) connected to a common edge cloud. Tractable expressions for both effective capacity and energy efficiency performance are derived, which show that the proposed structure can improve QoS guarantees with a lower cost of local storage. Furthermore, to fully explore the potential of the proposed cluster content caching structure, the joint design of resource allocation and RRH association is optimized, and two distributed algorithms are accordingly proposed. Simulation results verify the accuracy of the analytical results and show the performance gains achieved by cluster content caching in C-RANs.
Scheduling Algorithms Based on Resource Fragmentation for Advance Reservation Tasks

Advance reservation is an important method to guarantee the quality of service in Grid-like distributed systems. However, reserved jobs will make resource into fragments and decrease utilization. In order to minimize the negative effects of advance reservations, the authors analyzed the generation of resource fragments during reservation and investigated their influence on advance reservation requests in a quantitative way. Based on the quantification, two new scheduling algorithms, Resource Fragment-aware Best Fit (FSB) and Resource Fragment-aware Worst Fit (FSW), were proposed and their performances were investigated via comprehensive simulations. In simulation, mean job size, deadline factor, system load and sever number were chosen as control factors, and the performances of the algorithms were analyzed in terms of job acceptance rate, resource utilization and slowdown. We also compared FSB and FSW with Best Fit, First Fit, Min_LIP and Min_TIP. The simulations show that FSW and FSB can provide higher job acceptance rate, especially under heavy system load.
Injectable, degradable, electroactive nanocomposite hydrogels containing conductive polymer nanoparticles for biomedical applications

Injectable electroactive hydrogels (eGels) are promising in regenerative medicine and drug delivery, however, it is still a challenge to obtain such hydrogels simultaneously possessing other properties including uniform structure, degradability, robustness, and biocompatibility. An emerging strategy to endow hydrogels with desirable properties is to incorporate functional nanoparticles in their network. Herein, we report the synthesis and characterization of an injectable hydrogel based on oxidized alginate (OA) crosslinking gelatin reinforced by electroactive tetraaniline-graft-OA nanoparticles (nEOAs), where nEOAs are expected to impart electroactivity besides reinforcement without significantly degrading the other properties of hydrogels. Assays of transmission electron microscopy, 1H nuclear magnetic resonance, and dynamic light scattering reveal that EOA can spontaneously and quickly self-assemble into robust nanoparticles in water, and this nanoparticle structure can be kept at pH 3~9. Measurement of the gel time by rheometer and the stir bar method confirms the formation of the eGels, and their gel time is dependent on the weight content of nEOAs. As expected, adding nEOAs to hydrogels does not cause the phase separation (scanning electron microscopy observation), but it improves mechanical strength up to ~8 kPa and conductivity up to ~10−6 S/cm in our studied range. Incubating eGels in phosphate-buffered saline leads to their further swelling with an increase of water content <6% and gradual degradation. When growing mesenchymal stem cells on eGels with nEOA content ≤14%, the growth curves and morphology of cells were found to be similar to that on tissue culture plastic; when implanting these eGels on a chick chorioallantoic membrane for 1 week, mild inflammation response appeared without any other structural changes, indicating their good in vitro and in vivo biocompatibility. With injectability, uniformity, degradability, electroactivity, relative robustness, and biocompatibility, these eGels may have a huge potential as scaffolds for tissue regeneration and matrix for stimuli responsive drug release.
Steroid-Induced Diabetes: Is It Just Unmasking of Type 2 Diabetes?

Aims. We compared the demographic profile and clinical characteristics of individuals with new onset steroid-induced diabetes (NOSID) to Type 2 diabetes (T2DM) patients with and without steroid treatment. Methods. The demographic profile and clinical characteristics of 60 individuals who developed NOSID were examined and matched to 60 type 2 diabetes patients receiving steroid therapy (T2DM+S) and 360 diabetic patients not on steroids (T2DM) for age, duration of diabetes, HbA1c, gender, and ethnicity. Results. Patients who developed NOSID had less family history of diabetes (P ≤ 0.05) and were less overweight (P ≤ 0.02). NOSID was more commonly treated with insulin. Despite a matching duration of diabetes and glycaemic control, significantly less retinopathy was found in the group of patients with NOSID (P < 0.03). Conclusions. It appears that steroid treatment primarily precipitated diabetes in a group of individuals otherwise less affected by risk factors of diabetes at that point in time, rather than just opportunistically unmasking preexisting diabetes. Furthermore, the absence of retinopathy suggests that patients with NOSID had not been exposed to long periods of hyperglycaemia. However, the impact of the underlying conditions necessitating steroid treatment and concomitant medications such as immunosuppressants on diabetes development remain to be defined.
UsabML: formalising the exchange of usability findings

During the iterative development of interactive software, formative evaluation is often performed to find and fix usability problems early on. The output of a formative evaluation usually takes the form of a prioritised list of usability findings, each finding typically consisting of a description of the problem, how often it occurred, and sometimes a recommendation for a possible solution. Unfortunately, the valuable results of formative evaluations are usually collected into a written document. This makes it extremely difficult to automate the handling of usability findings. A more formalised, electronic format for the handover of usability findings would make much more sense. UsabML is a formalised structure for reporting usability findings expressed in XML. It allows usability experts and software engineers to import usability findings into bug (issue) tracking systems, to associate usability issues with parts of source code, and to track progress in fixing them.
A Linear Cheeger Inequality using Eigenvector Norms

The Cheeger constant, $h_G$, is a measure of expansion within a graph. The classical Cheeger Inequality states: $\lambda_{1}/2 \le h_G \le \sqrt{2 \lambda_{1}}$ where $\lambda_1$ is the first nontrivial eigenvalue of the normalized Laplacian matrix. Hence, $h_G$ is tightly controlled by $\lambda_1$ to within a quadratic factor. We give an alternative Cheeger Inequality where we consider the $\infty$-norm of the corresponding eigenvector in addition to $\lambda_1$. This inequality controls $h_G$ to within a linear factor of $\lambda_1$ thereby providing an improvement to the previous quadratic bounds. An additional advantage of our result is that while the original Cheeger constant makes it clear that $h_G \to 0$ as $\lambda_1 \to 0$, our result shows that $h_G \to 1/2$ as $\lambda_1 \to 1$.
PARS — An efficient congestion-Aware Routing method for Networks-on-Chip

The performance of NoCs (Networks-On-Chip) highly relies on the routing algorithm. Despite the higher implementation complexity compared with deterministic routing, adaptive routing has several merits, such as lower latency, higher throughput and better fault-tolerance performance. Most of the existing adaptive routing algorithms are based on the comparison of the horizontal and vertical congestion status in the network. However the performance of adaptive routing schemes suffers from the inadequate global congestion information. To address this issue, we proposed a novel routing algorithm with a congestion aware subnetwork to obtain more accurate non-local congestion information. This subnetwork will propagate the congestion information along the paths directly towards the destination. To find a less congested path, PARS (Path-Aware Routing Scheme) uses the congestion information of paths in a straight direction towards the destination rather than local congestion information. The simulation results reveal that the new presented scheme can offer better performance under different traffic profiles with a small hardware overhead.
How Is Code Recommendation Applied in Android Development: A Qualitative Review

Code recommendation has been an indispensable feature of IDE (Integrated Development Environment) for modern software developers. Android developers especially require code recommendation support to ensure high development efficiency and quality, as Android applications are developed based on Android application framework and thus are more pattern-based. Many techniques and tools have been developed to support code recommendation in different ways. However, it is not clear how these techniques and tools can be used in Android development and whether Android development can be well supported by them. In this paper, we present a qualitative review on code recommendation techniques and tools with the focus of support for Android development. We first categorize code recommendation techniques and tools reported in literatures and then evaluate them towards the requirements of Android development. The evaluation results enable us to draw a comprehensive image of how code recommendation benefits Android development and also the deficiencies of state-of-the-art code recommendation techniques in meeting specific requirements of Android development. Based on the evaluation, a comprehensive discussion is presented to suggest possible improvement and future research directions of code recommendation techniques.
Characteristics of smokers and predictors of quitting in a smoking cessation clinic in Guangzhou, China.

BACKGROUND Smoking cessation programs are well established in the West, but reports on smoking cessation clinics (SCCs) from China are lacking. On the basis of the Hong Kong experience and with strong support from Guangzhou Health Bureau, we established the first SCC in Guangzhou, China. The objective was to describe the characteristics of smokers, measure quit rates and examine predictors of successful quitting. METHODS During 2006-08, 220 smokers received individual counseling following the five A's and five R's. No medications were used. RESULTS At baseline, the mean (SD) age was 40 (14) years. Most (96%) were males, married (73%), currently employed (75%), college educated or above (54%); 77% had previous quitting attempts. By 14 May 2008, 195 reached the 6 months follow-up period. Of them, 79% (151/195) were successfully followed up, and 46 had quit. By intention to treat, the 6-month 7-day point prevalence quit rate was 24% [95% confidence interval (CI) 18-30%]. Smokers with more confidence in quitting or were at action stage were more successful in quitting with adjusted odds ratio of 2.39 (95% CI 1.01-5.30) and 5.50 (95% CI 1.08-28) respectively. CONCLUSIONS A pilot-model clinic free of charge and with systemic data collection, follow-up and evaluation should be a starting point for smoking cessation program in low-income countries.
The experiences of adults living with epilepsy : an interpretive description

iii Acknowledgements . iv List of Tables . vii List of Appendices . viii Chapter 1: Introduction . 1 Purpose . 2 Rationale . 3 Significance of the Study . 3 Chapter 2: Literature Review . 5 Introduction . 5 Physical Health Dimension . 5 Social Health Dimension . 11 Emotional Health Dimension . 15 Spiritual Health Dimension . 18 Summary . 20 Chapter 3: Research Design and Methodology . 22 Introduction . 22 Methodology . 22 Setting . 24 Sampling . 24 Data Collection Methods . 27 Semi-structured interviews . 27 Unstructured research journaling . 28 Documentation.29 Data Analysis . 29 Rigor . 32 Epistemological integrity . 32 Representative credibility . 33 Analytic logic.33 Interpretive authority.33 Ethical Considerations . 34 vi Chapter 4: Findings . 36 Introduction . 36 Past . 37 Present . 40 Threats to Well-Being . 40 Developing a ‘mind-set’. 42 Protecting self.42 Securing belonging.44 Future Life Vision . 45 Summary . 47 Chapter 5: Discussion . 49 Introduction . 49 Epilepsy as a Life Journey . 49 Past . 51 Present . 55 Future . 58 Limitations . 60 Conclusions . 60 References . 62
Multi-linear data-driven dynamic hair model with efficient hair-body collision handling

We present a data-driven method for learning hair models that enables the creation and animation of many interactive virtual characters in real-time (for gaming, character pre-visualization and design). Our model has a number of properties that make it appealing for interactive applications: (i) it preserves the key dynamic properties of physical simulation at a fraction of the computational cost, (ii) it gives the user continuous interactive control over the hair styles (e.g., lengths) and dynamics (e.g., softness) without requiring re-styling or re-simulation, (iii) it deals with hair-body collisions explicitly using optimization in the low-dimensional reduced space, (iv) it allows modeling of external phenomena (e.g., wind). Our method builds on the recent success of reduced models for clothing and fluid simulation, but extends them in a number of significant ways. We model motion of hair in a conditional reduced sub-space, where the hair basis vectors, which encode dynamics, are linear functions of user-specified hair parameters. We formulate collision handling as an optimization in this reduced sub-space using fast iterative least squares. We demonstrate our method by building dynamic, user-controlled models of hair styles.
Longevity of clonal plants: why it matters and how to measure it.

BACKGROUND Species' life-history and population dynamics are strongly shaped by the longevity of individuals, but life span is one of the least accessible demographic traits, particularly in clonal plants. Continuous vegetative reproduction of genets enables persistence despite low or no sexual reproduction, affecting genet turnover rates and population stability. Therefore, the longevity of clonal plants is of considerable biological interest, but remains relatively poorly known. SCOPE Here, we critically review the present knowledge on the longevity of clonal plants and discuss its importance for population persistence. Direct life-span measurements such as growth-ring analysis in woody plants are relatively easy to take, although, for many clonal plants, these methods are not adequate due to the variable growth pattern of ramets and difficult genet identification. Recently, indirect methods have been introduced in which genet size and annual shoot increments are used to estimate genet age. These methods, often based on molecular techniques, allow the investigation of genet size and age structure of whole populations, a crucial issue for understanding their viability and persistence. However, indirect estimates of clonal longevity are impeded because the process of ageing in clonal plants is still poorly understood and because their size and age are not always well correlated. Alternative estimators for genet life span such as somatic mutations have recently been suggested. CONCLUSIONS Empirical knowledge on the longevity of clonal species has increased considerably in the last few years. Maximum age estimates are an indicator of population persistence, but are not sufficient to evaluate turnover rates and the ability of long-lived clonal plants to enhance community stability and ecosystem resilience. In order to understand the dynamics of populations it will be necessary to measure genet size and age structure, not only life spans of single individuals, and to use such data for modelling of genet dynamics.
Delivering improved multiple services to IP traffic in DiffServ networks

This short paper presents the results of a research on the design, implementation and analysis of a packet scheduling mechanism for multi-traffic classes in the context of DiffServ networks. Our studies aimed at providing QoS assurances to real-time applications over IP networks. We began by identifying that QoS performance guarantees per-class of traffic aggregate are inherently required in the core of the Internet. We assume that traffic classification based on the application QoS requirements is an indispensable feature for providing QoS guarantees to a wide variety of real-time applications like voice over IP (VoIP) and video conferencing due to the scalability issues.
Smoking, smoking cessation, and lung cancer in the UK since 1950: combination of national statistics with two case-control studies

Abstract Objective and design: To relate UK national trends since 1950 in smoking, in smoking cessation, and in lung cancer to the contrasting results from two large case-control studies centred around 1950 and 1990. Setting: United Kingdom. Participants: Hospital patients under 75 years of age with and without lung cancer in 1950 and 1990, plus, in 1990, a matched sample of the local population: 1465 case-control pairs in the 1950 study, and 982 cases plus 3185 controls in the 1990 study. Main outcome measures: Smoking prevalence and lung cancer. Results: For men in early middle age in the United Kingdom the prevalence of smoking halved between 1950 and 1990 but the death rate from lung cancer at ages 35–54 fell even more rapidly, indicating some reduction in the risk among continuing smokers. In contrast, women and older men who were still current smokers in 1990 were more likely than those in 1950 to have been persistent cigarette smokers throughout adult life and so had higher lung cancer rates than current smokers in 1950. The cumulative risk of death from lung cancer by age 75 (in the absence of other causes of death) rose from 6% at 1950 rates to 16% at 1990 rates in male cigarette smokers, and from 1% to 10% in female cigarette smokers. Among both men and women in 1990, however, the former smokers had only a fraction of the lung cancer rate of continuing smokers, and this fraction fell steeply with time since stopping. By 1990 cessation had almost halved the number of lung cancers that would have been expected if the former smokers had continued. For men who stopped at ages 60, 50, 40, and 30 the cumulative risks of lung cancer by age 75 were 10%, 6%, 3%, and 2%. Conclusions: People who stop smoking, even well into middle age, avoid most of their subsequent risk of lung cancer, and stopping before middle age avoids more than 90% of the risk attributable to tobacco. Mortality in the near future and throughout the first half of the 21st century could be substantially reduced by current smokers giving up the habit. In contrast, the extent to which young people henceforth become persistent smokers will affect mortality rates chiefly in the middle or second half of the 21st century.
Software security: Vulnerabilities and countermeasures for two attacker models

History has shown that attacks against network-connected software based systems are common and dangerous. An important fraction of these attacks exploit implementation details of the software based system. These attacks - sometimes called low-level attacks - rely on characteristics of the hardware, compiler or operating system used to execute software programs to make these programs misbehave, or to extract sensitive information from them. With the increased Internet-connectivity of embedded devices, including industrial control systems, sensors as well as consumer devices, there is a substantial risk that similar attacks will target these devices. This tutorial paper explains the vulnerabilities, attacks and countermeasures relevant for low-level software security. The paper discusses software security for two different attacker models: the classic model of an attacker that can only interact with the program by providing input and reading output, and the more recent and challenging model of an attacker that controls part of the execution platform on which the software runs, for instance because the attacker has compromised the operating system, or some of the libraries that the software under attack relies on.
Abstract 808: Intrinsic gene expression profiles of gliomas are a better predictor of survival than histology

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Treatment decisions in patients rely mainly on histological classification and clinical parameters. However, differences between histological subclasses and grades are subtle, and classifying gliomas is subject to a large inter-observer variability. To improve current classification standards, we have performed gene expression profiling on a large cohort of glioma samples of all histological subtypes and grades. We identified seven distinct molecular subgroups that correlate with survival. These include two favorable prognostic subgroups (median survival >4.7 years), two with intermediate prognosis (median survival 1-4 years), two with poor prognosis (median survival <1 year), and one control group. The intrinsic molecular subtypes of glioma are different from histological subgroups and correlate better to patient survival. The prognostic value of molecular subgroups was validated on five independent sample cohorts (TCGA, REMBRANDT, [GSE12907][1], [GSE4271][2], and Li et al.). The power of intrinsic subtyping is demonstrated by its ability to identify a subset of prognostically favorable tumors within an external dataset that contains only histologically confirmed glioblastomas. Specific genetic changes (EGFR amplification, IDH1 mutation, 1p/19q LOH) segregate in distinct molecular subgroups. We identified a subgroup with molecular features associated with secondary glioblastoma, suggesting that different genetic changes drive gene expression profiles. Finally, we assessed response to treatment in molecular subgroups. Our data provides compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histological classification. Molecular classification therefore may aid diagnosis and can guide clinical decision making. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 808. [1]: /lookup/external-ref? link_type=NCBIGEO&access_num=GSE12907&atom=%2Fcanres%2F70%2F8_Supplement%2F808.atom [2]: /lookup/external-ref? link_type=NCBIGEO&access_num=GSE4271&atom=%2Fcanres%2F70%2F8_Supplement%2F808.atom